Faculty Profiles - Deguchi Daisuke

Presentations -

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講義スライドのコンテンツ解析に基づく講義動画の自動生成に関する予備検討

水上皓太, 出口大輔, 久徳遙矢, 峰松翼, 村瀬洋

教育学習支援情報システム研究会(CLE) 2025.3.21

Multi-group Vision Semantic Centroid for Semantic Segmentation International conference

Jialei Chen, Daisuke Deguchi, Chenkai Zhang, Zhenzhen Quan, Seigo Ito, Hiroshi Murase

Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2025) 2025.2.18

Event date： 2025

Language：English Presentation type：Oral presentation (general)

Venue：Sogang University, Seoul, Korea

Multi-media processing has achieved great success based on
semantic segmentation. Semantic segmentation can be viewed as pixel-
clustering based on semantic prototypes. However, existing methods fo-
cus more on consistent semantics while ignoring the consistency in vi-
sion, making this task challenging. Motivated by the success of discrete
visual representation learning, we propose Multi-group Visual Semantic
Centroid (MVSC) to better cluster the pixels while maintaining consis-
tent semantics of the dense features for any image encoder. Specifically,
we randomly initialize multiple groups of prototypes as multi-groups in
visual space. The visual features are also randomly split into the same
groups and forced to be aligned with the corresponding prototypes. Then
these visual prototypes are projected into the semantic space and super-
vised by the same classifier as the dense features. Compared with existing
methods, MVSC further considers the visual space and thus facilitates
the task. Experimental results on COCO-Stu! show great improvements
compared with previous methods.

A Cross-Modal Knowledge Distillation Approach for RGB-to-Infrared Video Action Recognition International conference

Zhenzhen Quan, Daisuke Deguchi, Jialei Chen, Chenkai Zhang, Yujun Li, Seigo Ito, Hiroshi Murase

Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2025) 2025.2.18

Object Detection using In-Vehicle Camera Images with Object Attributes Constraints

星谷那月, Daisuke Deguchi, Jialei Chen, Hiroshi Murase, 伊藤誠悟

IEICE Technical Report (MVE) 2025.3.5

複数歩行者間のインタラクション理解に向けた気づき認識データセットの構築

辰己弘征, 出口大輔, 村瀬洋, 伊藤誠悟

メディアエクスペリエンス・バーチャル環境基礎研究会(MVE) 2025.3.5

学習活動ログと講義スライドの併用による早期At-risk 検出

尾﨑優也, 出口大輔, 久徳遙矢, 村瀬洋

教育学習支援情報システム研究会(CLE) 2025.3.20

A preliminary study on colorized NeRF with grayscale images.

水上皓太, Daisuke Deguchi, Hiroshi Murase

2024.3.17

A Preliminary Study on Pre-training for Improved Explainability in End-to-End Driving Models

Chenkai Zhang, Daisuke Deguchi, Jialei Chen, Hiroshi Murase

Pattern Recognition and Media Understanding (PRMU) 2024.1.26

Event date： 2024

Language：English Presentation type：Oral presentation (general)

Venue：Keio University

In the realm of autonomous driving, end-to-end models (E2EDMs) have gained prominence due to their high predictive accuracy. Such accuracy is attributed to the utilization of a backbone pre-trained on large datasets, subsequently fine-tuned on autonomous driving datasets. However, the inherent “black box” nature of these E2EDMs poses significant challenges in terms of explainability. Current methodologies predominantly focus on generating visual explanations for the E2EDMs’ decision-making process. Numerous approaches aim to enhance the explainability of these E2EDMs by fine-tuning with complicated architectures, supplemented by additional information, e.g., object position to develop more explainable E2EDMs. In this study, we diverge from the conventional approaches where significant effort is placed during the fine-tuning phase of E2EDMs. Our method focuses on training backbones before the fine-tuning phase. This preemptive strategy enables us to fine-tune more explainable E2EDMs without the need for additional information or complex training techniques.

Pedestrian's Gaze Object Detection in Traffic Scene International conference

Hiroto Murakami, Jialei Chen, Daisuke Deguchi, Takatsugu Hirayama, Yasutomo Kawanishi, Hiroshi Murase

19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP) 2024 2024.2.27

Event date： 2024

Language：English Presentation type：Poster presentation

Venue：Rome, Italy

In this paper, we present a new task of detecting an object that a target pedestrian is gazing at in a traffic scene called PEdestrian's Gaze Object (PEGO). We argue that the detection of gaze object can provide important information for pedestrian's behavior prediction and can contribute to the realization of automated vehicles. For this task, we construct a dataset of in-vehicle camera images with annotations of the objects that pedestrians are gazing at. Also, we propose a Transformer-based method called PEGO Transformer to solve the PEGO detection task. The PEGO Transformer directly performs gaze object detection with the utilization of whole-body features without a high-resolution head image and a gaze heatmap which the traditional methods rely on. Experimental results showed that the proposed method could estimate pedestrian's gaze object accurately even if various objects exist in the scene.

Comprehensive Evaluation of End-to-End Driving Model Explanations for Autonomous Vehicles International conference

Chenkai Zhang, Daisuke Deguchi, Jialei Chen, Hiroshi Murase

19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP) 2024 2024.2.27

Event date： 2024

Language：English Presentation type：Oral presentation (general)

Venue：Precise House Mantegna Roma

Deep learning technology has rapidly advanced, leading to the development of End-to-End driving models (E2EDMs) for autonomous vehicles with high prediction accuracy. To comprehend the prediction results of these E2EDMs, one of the most representative explanation methods is attribution-based. There are two kinds of attribution-based explanation methods: pixel-level and object-level. Usually, the heatmaps illustrate the importance of pixels and objects in the prediction results, serving as explanations for E2EDMs. Since there are many attribution-based explanation methods, evaluation methods are proposed to determine which one is better at improving the explainability of E2EDMs.
Fidelity measures the explanation's faithfulness to the model's prediction method, which is a bottommost property. However, no evaluation method could measure the fidelity difference between object-level and pixel-level explanations, making the current evaluation incomplete. In addition, without considering fidelity, previous evaluation methods may advertise manipulative explanations that solely seek human satisfaction (persuasibility). Therefore, we propose an evaluation method that further considers fidelity, our method enables a comprehensive evaluation that proves the object-level explanations genuinely outperform pixel-level explanations in fidelity and persuasibility, thus could better improve the explainability of the E2EDMs.

交通シーン画像からの歩行者の注視対象物推定

村上大斗, 陳嘉雷, 出口大輔, 平山高嗣, 川西康友, 村瀬洋

動的画像処理実利用化ワークショップ(DIA) 2024.3.4

Event date： 2024

Language：Japanese Presentation type：Oral presentation (general)

Venue：別府国際コンベンションセンタービーコンプラザ

注視対象物推定は，自動運転車両の実現において不可欠な歩行者の行動予測のための重要な要素である．本発表では，交通シーンで歩行者が注視している物体（PEdestrians' Gaze Object: PEGO）を推定するPEGO Transformer V2を提案する．従来手法の多くは，高解像度の頭部画像と視線ヒートマップを用いて歩行者の注視対象物を推定している．しかしながら，遠方にいる歩行者に対して，高解像度の頭部画像を得られないため推定精度が低いという問題があった．そこでPEGO Transformer V2は，歩行者全身の特徴に加え，歩行者位置情報も活用することで性能改善を図る．実験の結果，提案手法であるPEGO Transformer V2は，シーン中の歩行者ごとにそれぞれ正しい注視対象物を推定できることを確認した．

A preliminary study on front image generation from back by diffusion model

松雄なずな, Daisuke Deguchi, Hiroshi Murase

2024.3.17

A Study on Fixed Orthogonal Prototype Classifier for Semantic Segmentation

Jialei Chen, Daisuke Deguchi, Chenkai Zhang, Xu Zheng, Hiroshi Murase

Pattern Recognition and Media Understanding (PRMU) 2024.1.26

Distill from CLIP by Token Alignment for Inductive Zero-shot Semantic Segmentation

Jialei Chen, Daisuke Deguchi, Chenkai Zhang, Zhenzhen Quan, Hiroshi Murase

2024.8.9

Enhancing Explainability of End-to-End Autonomous Driving Models through additional fine-tuning

Chenkai Zhang, Daisuke Deguchi, Jialei Chen, Hiroshi Murase

27th Meeting on Image Recognition and Understanding (MIRU2024) 2024.8.9

Event date： 2024

Language：English Presentation type：Poster presentation

Venue：熊本城ホール（熊本県熊本市中央区桜町3番40号）

In autonomous driving, end-to-end driving models (E2EDMs) have become increasingly popular due to their exceptional predictive performance. This performance stems from leveraging a backbone that is pre-trained on large datasets and then fine-tuned for driving tasks. However, the opaque nature of these E2EDMs presents a challenge to explainability, thus visual explanations are created to shed light on the decision-making process of E2EDMs. Currently, these E2EDMs have been made more explainable by fine-tuning the driving tasks along with a side task designed for explainability. This side task for explainability requires complex structures with auxiliary data, such as the location of objects.
In this paper, we argue that a more effective approach to enhancing the explainability of E2EDMs is to design a fine-tuning specifically focused on explainability. We propose CROp-based COntrastive DIscriminative LEarning (CROCODILE) to enhance a backbone’s capability to accurately identify object features during this additional fine-tuning for explainability. By adopting CROCODILE, we can develop more explainable E2EDMs without relying on auxiliary data or complex structures in the fine-tuning for driving tasks. Our experimental results confirm that our approach enhances the explainability of E2EDMs.

A Decoupled Knowledge Distillation Approach for RGB-to-Infrared Video Action Recognition

Zhenzhen Quan, Jialei Chen, Chenkai Zhang, Daisuke Deguchi, Hiroshi Murase

27th Meeting on Image Recognition and Understanding (MIRU2024) 2024.8.9

学習活動ログを用いたAt-risk 学生の早期検出：学習活動予測ネットワークの活用

尾﨑優也, 出口大輔, 久徳遙矢, 村瀬洋

第27回画像の認識・理解シンポジウム(MIRU2024) 2024.8.9

Front Image Generation from Back by Diffusion Model

Nazuna Matsuo, Daisuke Deguchi, Hiroshi Murase

27th Meeting on Image Recognition and Understanding (MIRU2024) 2024.8.9

Centroid Module for Shaping Feature Space in Semantic Segmentation International conference

Jialei Chen, Daisuke Deguchi, Chenkai Zhang, Hiroshi Murase

3rd Asia Conference on Cloud Computing, Computer Vision and Image Processing (3CVIP 2024) 2024.3.23

A construction of colorized NeRF with grayscale images

Kota Mizukami, Daisuke Deguchi, Hiroshi Murase

27th Meeting on Image Recognition and Understanding (MIRU2024) 2024.8.6

CROCODILE: Crop-based Contrastive Discriminative Learning for Enhancing Explainability of End-to-End Driving Models International conference

Chenkai Zhang, Daisuke Deguchi, Jialei Chen, Zhenzhen Quan, Hiroshi Murase

ACCV Workshop on Machine Learning and Computing for Visual Semantic Analysis (MLCSA2024) 2024.12.8

Early prediction of At-risk students through Learning-Activity Forecasting International conference

Yuya Ozaki, Daisuke Deguchi, Haruya Kyutoku, Hiroshi Murase

32nd International Conference on Computers in Education (ICCE2024) 2024.11.27

体格を考慮した歩き方からの手荷物の主観的重さ推定の検討

水野雅也, 藤田倫弘, 川西康友, 出口大輔, 村瀬洋

パターン認識・メディア理解研究会(PRMU) 2023.3.2

NeRFモデルを用いた初期値非依存なカメラポーズ推定

尾﨑優也, 出口大輔, 川西康友, 村瀬洋

研究報告コンピュータビジョンとイメージメディア（CVIM） 2023.3.3

歩行者の注視対象データセットの構築

村上大斗, 出口大輔, 平山高嗣, 川西康友, 村瀬洋

コンピュータビジョンとイメージメディア研究会(CVIM) 2023.3.3

Eye-contact Transformer: Eye contact detection of distant pedestrians using a sequence of skeletons and scene features

Ryusei Hata, Daisuke Deguchi, Takatsugu Hirayama, Yasutomo Kawanishi, Hiroshi Murase

IEICE Technical Report (PRMU) 2023.3.3

Unknown Object Segmentation by View Independent Scene Change Detection

Jiaxin Li, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (PRMU) 2023.3.3

Human actionrecognition from images

Daisuke Deguchi

2023.1.24

A Preliminary Study on View Independent Panoptic Scene Change Detection International conference

Jiaxin Li, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

International Workshop on Advanced Image Technology (IWAIT) 2023 2023.1.16

End-to-End gaze grounding from a person pictured from behind International conference

Hayato Yumiya, Daisuke Deguchi, Yasutomo Kawanishi, Hiroshi Murase

18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications 2023.2.21

Subjective Baggage-Weight Estimation from Gait: Can You Estimate How Heavy the Person Feels? International conference

Masaya Mizuno, Tomohiro Fujita, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP) 2023 2023.2.20

交通シーンにおける歩行者の注視対象物推定の検討

村上大斗, 陳嘉雷, 出口大輔, 平山高嗣, 川西康友, 村瀬洋

第26回画像の認識・理解シンポジウム(MIRU2023) 2023.7.26

Refined Objectification for Improving End-to-End Driving Model Explanation Persuasibility International conference

Chenkai Zhang, Daisuke Deguchi, Hiroshi Murase

2023 IEEE Intelligent Vehicles Symposium (IV2023) 2023.6.5

Explainability Enhancement module for End-to-End Driving Models by Focusing on the important objects

Chenkai Zhang, Daisuke Deguchi, Hiroshi Murase

26th Meeting on Image Recognition & Understanding (MIRU2023) 2023.7.26

少量の学習ログからの成績予測モデル構築に関する予備的検討

尾﨑優也, 出口大輔, 村瀬洋, 川西康友, 久徳遙矢

第172回コンピュータと教育・第41回教育学習支援情報システム合同研究発表会 2023.12.3

Explainability Enhancement module for End-to-End Driving Models by Focusing on the important objects

Chenkai Zhang, Daisuke Deguchi, Hiroshi Murase

26th Meeting on Image Recognition & Understanding (MIRU2023) 2023.7.26

交通シーンにおける歩行者の注視対象物推定の検討

村上大斗, 陳嘉雷, 出口大輔, 平山高嗣, 川西康友, 村瀬洋

第26回画像の認識・理解シンポジウム(MIRU2023) 2023.7.26

先進ビークル研究 ―カメラを用いた自車位置推定等ー

出口大輔

革新的製品創出サロン 2023.9.29

人物姿勢と注視対象配置制約を使用した後ろ向き人物の注視領域推定

弓矢隼大, 出口大輔, 川西康友, 村瀬洋

情報処理学会全国大会第84回 2022.3.5

Active Learning for Human Pose Estimation based on Temporal Pose Continuity International conference

Taro Mori, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase, Tetsuo Inoshita

International Workshop on Advanced Image Technology (IWAIT) 2022 2022.1.6

歩容からの身体特徴と動作特徴の分離による手荷物の物理的・主観的重さ推定

水野雅也, 川西康友, 出口大輔, 村瀬洋

第25回画像の認識・理解シンポジウム(MIRU2022) 2022.7.27

Intuitive Gait Modeling using Mimetic-Words for Gait Description and Generation International conference

Hirotaka Kato, Takatsugu Hirayama, Keisuke Doman, Ichiro Ide, Yasutomo Kawanishi, Takahiro Komamizu, Daisuke Deguchi, Hiroshi Murase

2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR) 2022.8.3

サムネイル画像への見出しレイアウト生成

成川喬朗, 出口大輔, 川西康友, 村瀬洋

第25回画像の認識・理解シンポジウム(MIRU2022) 2022.7.28

時空間骨格情報を用いた遠方歩行者のアイコンタクト検出

畑隆聖, 出口大輔, 平山高嗣, 川西康友, 村瀬洋

第25回画像の認識・理解シンポジウム(MIRU2022) 論文集 2022.7.27

Detection of distant eye-contact using spatio-temporal pedestrian skeletons International conference

Ryusei Hata, Daisuke Deguchi, Takatsugu Hirayama, Yasutomo Kawanishi, Hiroshi Murase

The 25th IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2022) 2022.9.26

Analysis of Gaze while Viewing Videos at Various Playback Speeds International conference

Hideaki Takahira, Yasutomo Kawanishi, Takatsugu Hirayama, Hiroshi Murase, Daisuke Deguchi

International Display Workshops 2022.12.15

Event date： 2022

Language：English Presentation type：Poster presentation

Venue：Fukuoka International Congress Center

We analyze gaze while viewing videos at various playback speeds.
The aims of this paper are to evaluate the comprehension and viewability of videos.
In our experiment, we used 0.75x to 3.0x speed, and measured gaze.
We report differences in gaze behavior among different playback speeds in viewing same video.

Detection of Birds in a 3D Environment Referring to Audio-Visual Information International conference

Yasutomo Kawanishi, Ichiro Ide, Baidong Chu, Chihaya Matsuhira, Marc A. Kastner, Takahiro Komamizu, Daisuke Deguchi

18th IEEE International Conference on Advanced Video and Signal-Based Surveillance 2022.11.29

Event date： 2022

Language：English Presentation type：Oral presentation (general)

Venue：Universidad Autónoma de Madrid (Hybrid)

We propose a method to detect birds in a 3D environment referring to both audio information observed from a microphone array and visual information observed from a panorama camera. In general, in panorama images, birds appear relatively too small to be detected accurately even with the state-of-the-art deep learning models. Thus, the proposed method takes a two step approach where the birds are first roughly located referring to audio information by Sound Source Localization (SSL), and then image detection is applied within its vicinity. Through evaluation on a dataset annotated with bounding boxes surrounding the birds, we show that the proposed method improves detection performance of birds that appear in relatively small sizes in the image, in both accuracy and processing speed.

DOI： 10.1109/AVSS56176.2022.9959510

人物姿勢に着目した後ろ向き人物の注視領域推定

弓矢隼大, 出口大輔, 川西康友, 村瀬洋

コンピュータビジョンとイメージメディア研究会(CVIM) 2022.11.19

A Preliminary Study on 4D Scene Modeling from Live-action Video Including Pedestrians

田中来樹, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

IEICE General Conference 2021.3.12

LFIR2Pose: Pose Estimation from an Extremely Low-Resolution FIR Image Sequence International conference

Saki Iwata, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomoyoshi Aizawa

25th International Conference on Pattern Recognition 2021.1.13

Event date： 2021

Language：English Presentation type：Poster presentation

Venue：Milan, Italy (Virtual)

In this paper, we propose a method for human pose estimation from a Low-resolution Far-InfraRed (LFIR) image sequence captured by a 16 × 16 FIR sensor array. Human body estimation from such a single LFIR image is a hard task. For training the estimation model, annotation of the human pose to the images is also a difficult task for human. Thus, we propose the LFIR2Pose model which accepts a sequence of LFIR images and outputs the human pose of the last frame, and also propose an automatic annotation system for the model training. Additionally, considering that the scale of human body motion is largely different among body parts, we also propose a loss function focusing on the difference. Through an experiment, we evaluated the human pose estimation accuracy using an original data set, and confirmed that human pose can be estimated accurately from an LFIR image sequence.

Median-Shape Representation Learning for Category-Level Object Pose Estimation in Cluttered Environments International conference

Hiroki Tatemichi, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Ayako Amma, Hiroshi Murase

25th International Conference on Pattern Recognition 2021.1.13

Event date： 2021

Language：English Presentation type：Poster presentation

Venue：Milan, Italy (Virtual)

In this paper, we propose an occlusion-robust pose
estimation method of an unknown object instance in an
object category from a depth image. In a cluttered
environment, objects are often occluded mutually. For
estimating the pose of an object in such a situation, a
method that de-occludes the unobservable area of the object
would be effective. However, there are two difficulties;
occlusion causes offset between the actual object center
and the center of its observable area, and different
instances in a category may have different shapes. To cope
with these difficulties, we propose a two-stage
Encoder-Decoder model to extract features with objects
whose centers are aligned to the image center. In the
model, we also propose the Median-shape Reconstructor as
the second stage to absorb shape variations in a category.
By evaluating the method with both a large-scale virtual
dataset and a real dataset, we confirmed the proposed
method achieves good performance on pose estimation of an
occluded object from a depth image.

OMEga-GAN: Object Manifold Embedding GAN for Image Generation by Disentangling Parameters into Pose and Shape Manifolds International conference

Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

25th International Conference on Pattern Recognition 2021.1.13

Event date： 2021

Language：English Presentation type：Poster presentation

Venue：Milan, Italy (Virtual)

In this paper, we propose Object Manifold Embedding GAN (Ω-GAN) to generate images of variously shaped and arbitrarily posed objects from a noise variable sampled from a distribution defined over the pose and the shape manifolds in a vector space. We introduce Parametric Manifold Sampling to sample noise variables from a distribution over the pose manifold to conditionally generate object images in arbitrary poses by tuning the pose parameter. We also introduce Object Identity Loss for clearly disentangling the pose and shape parameters, which allows us to maintain the shape of the object instance when only the pose parameter is changed. Through evaluation, we confirmed that the proposed Ω-GAN could generate variously shaped object images in arbitrary poses by changing the pose and shape parameters independently. We also introduce an application of the proposed method for object pose estimation, through which we confirmed that the object poses in the generated images are accurate.

A Study on Product Image Impression Estimation considering the Customer's Attributes

中本麻友, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, 中澤満, チェヨンナム, シュテンガービヨン

IEICE General Conference 2021.3.10

A Preliminary Study on Belongings Category and Weight Recognition based on Walking Skeleton Trajectory

水野雅也, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase, 井下哲夫

IEICE General Conference 2021.3.11

A Preliminary Study on Eye Contact Detection for Distant Pedestrians using an In-vehicle Camera

畑隆聖, Daisuke Deguchi, Takatsugu Hirayama, Yasutomo Kawanishi, Hiroshi Murase

IEICE General Conference 2021.3.11

個人差を考慮した歩き方からの手荷物の重さ推定の検討

水野雅也, 川西康友, 出口大輔, 村瀬洋

パターン認識・メディア理解研究会(PRMU) 2021.12.17

情報エントロピーにもとづく車両歩行者インタラクションモデルの検討

新村文郷, 赤井直紀, 川西康友, 平山高嗣, 劉海龍, 出口大輔, 村瀬洋

第22回計測自動制御学会システムインテグレーション部門講演会 2021.12.16

観衆の顔向きの時空間統合によるステージ上の注目対象及び注目度の推定

武田一馬, 川西康友, 平山高嗣, 出口大輔, 井手一郎, 村瀬洋, 柏野邦夫

パターン認識・メディア理解研究会(PRMU) 2021.12.17

人物姿勢と注視対象配置制約に基づく後ろ向き人物の注視領域推定

弓矢隼大, 川西康友, 出口大輔, 村瀬洋, 細野峻司

第24回画像の認識・理解シンポジウム(MIRU) 2021.7.30

人物姿勢と注視対象配置制約に基づく後ろ向き人物の注視領域推定

弓矢隼大, 川西康友, 出口大輔, 村瀬洋, 細野峻司

コンピュータビジョンとイメージメディア研究会(CVIM) 2021.5.21

人物姿勢と注視対象配置制約に基づく後ろ向き人物の注視領域推定

弓矢隼大, 川西康友, 出口大輔, 村瀬洋, 細野峻司

第24回画像の認識・理解シンポジウム(MIRU) 2021.7.30

歩き方の特徴に着目した所持物の種類・重さ認識の検討

水野雅也, 川西康友, 出口大輔, 村瀬洋, 井下哲夫

第24回画像の認識・理解シンポジウム(MIRU) 2021.7.29

Pointedness of an Image: Measuring How Pointy an Image is Perceived International conference

Chihaya Matsuhira, Marc A. Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

HCII 2021 2021.7.29

Event date： 2021

Language：English Presentation type：Poster presentation

Venue：Virtual

For computers to understand human perception, metrics that can capture human perception well are important. However, there are few metrics that characterize the visual perception of humans towards images. Therefore, in this paper, we propose a novel concept and a metric of pointedness of an image, which describes how pointy an image is perceived. The algorithm is inspired by the Features from Accelerated Segment Test (FAST) algorithm for corner detection which looks on the number of continuous neighboring darker pixels surrounding each pixel. We assume that this number would be proportional to the perceived pointedness in the region around the pixel. We evaluated our method towards how well it could capture the human perception of images. To compare the method with similar metrics that describe shapes, we prepared silhouette images of both artificial shapes and natural objects. The results showed that the proposed method gave nearly equivalent perceptual performance to other metrics and also worked in a larger variety of images.

DOI： https://doi.org/10.1007/978-3-030-78635-9_20

姿勢変化の連続性に着目した人物姿勢推定器の能動学習

森太郎, 出口大輔, 川西康友, 井手一郎, 村瀬洋, 井下哲夫

第24回画像の認識・理解シンポジウム(MIRU) 2021.7.28

Tell as you imagine: Sentence imageability-aware image captioning International conference

Kazuki Umemura, Marc A. Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

27th Int. Conf. on Multimedia Modeling (MMM2021) 2021.6.24

Imageability Estimation using Visual and Language Features International conference

Chihaya Matsuhira, Marc A. Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

2020 International Conference on Multimedia Retrieval 2020.10.28

Event date： 2020

Language：English Presentation type：Poster presentation

Venue：Dublin, Ireland (Virtual)

Imageability is a concept from Psycholinguistics quantizing the human perception of words. However, existing datasets are created through subjective experiments and are thus very small. Therefore, methods to automatically estimate the imageability can be helpful. For an accurate automatic imageability estimation, we extend the idea of a psychological hypothesis called Dual-Coding Theory, that discusses the connection of our perception towards visual information
and language information, and also focus on the relationship between the pronunciation of a word and its imageability. In this research, we propose a method to estimate imageability of words
using both visual and language features extracted from corresponding data. For the estimation, we use visual features extracted from low- and high-level image features, and language features extracted from textual features and phonetic features of words. Evaluations how that our proposed method can estimate imageability more accurately than comparative methods, implying the contribution of each feature to the imageability.

DOI： 10.1145/3372278.3390731

A study on image captioning considering its imageability

Kazuki Umemura, Marc Aurel Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2020.3.5

Typicality evaluation of food-type specific presentation

Masamu Nakamura, Yasutomo Kawanishi, Keisuke Doman, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2020.3.5

A Preliminary Study on Improving a Cyclist Detector Using Weakly Supervised Learning

Taro Mori, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

IEICE General Conference 2020.3.3

A Preliminary Study on Multi-Target Attention Degree Estimation based on the Movement of Gaze Points

Kazuma Takeda, Yasutomo Kawanishi, Takatsugu Hirayama, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hidehisa Nagano, Kunio Kashino

IEICE General Conference 2020.3.3

A Preliminary Study on Vehicle Localization Utilizing Multiple Driving Image Sequences

Yuta Goto, Haruya Kyutoku, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

IEICE General Conference 2020.3.3

SOANets: Encoder-Decoder based Skeleton Orientation Alignment Network for White Cane User Recognition from 2D Human Skeleton Sequence International conference

Naoki Nishida, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Jun Piao

International Conference on Computer Vision Theory and Applications (VISAPP) 2020 2020.2.27

Event date： 2020

Language：English Presentation type：Poster presentation

Venue：Grand Hotel Excelsior Malta

In recent years, various facilities have been deployed to support visually impaired people. However, accidents caused by visual disabilities still occur. In this paper, to support the visually impaired people in public areas, we aim to identify whether a pedestrian image sequence obtained by a surveillance camera indicates the presence of a white cane user by analyzing the temporal transition of a human skeleton represented as 2D coordinates. Our previously proposed method aligns the orientation of the human skeletons to various orientations and identifies a white cane user from the corresponding sequences, relying on multiple classifiers related to each orientation. The method employs an exemplar-based approach to perform the alignment. However, it heavily depends on the number of exemplars and consumes excessive memory. In this paper, we propose a method to align 2D human skeleton representation sequence to various orientations using the proposed Skeleton Orientation Alignment Networks (SOANets) based on an encoder-decoder model. Using SOANets, we can obtain 2D skeleton representation sequences aligned to various orientations, extract richer skeleton features, and recognize white cane users accurately. We conducted an experiment to confirm that the
proposed method improves the recognition rate by 16%, compared to the method that does not use the skeleton
orientation alignment.

Occlusion-Aware Skeleton Trajectory Representation for Abnormal Behavior Detection International conference

Onur Temuroglu, Yasutomo Kawanishi, Daisuke Deguchi, Takatsugu Hirayama, Ichiro Ide, Hiroshi Murase, Mayuu Iwasaki, Atsushi Tsukada

The International Workshop on Frontiers of Computer Vision (IW-FCV) 2020.2.20

Event date： 2020

Language：English Presentation type：Oral presentation (general)

Venue：指宿ふれあいプラザなのはな館

Surveillance cameras are expected to play a large role in the development of ITS technologies. They can be used to detect abnormally behaving individuals which can then be reported to drivers nearby. There are multiple works that tackle the problem of abnormal behavior detection. However, most of these works make use of appearance features which have redundant information and are susceptible to noise. While there are also works that make use of pose skeleton representation, they do not consider well how to handle cases with occlusions, which can occur due to the simple reason of pedestrian orientation preventing some joints from appearing in the frame clearly. In this paper, we propose a skeleton trajectory representation that enables handling of occlusions. We also propose a framework for pedestrian abnormal behavior detection that uses the proposed representation and detect relatively hard-to-notice anomalies such as drunk walking. The experiments we conducted show that our method outperforms other representation methods.

Browsing Visual Sentiment Datasets Using Psycholinguistic Groundings International conference

Marc Aurel Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Daisuke Deguchi, Hiroshi Murase

Lecture Note in Computer Science 2020.1.4

Event date： 2020

Language：English

Venue：Deajeon Convention Center, Daejeon, Korea

Recent multimedia applications commonly use text and imagery from Social Media for tasks related to sentiment research. As such, there are various image datasets for sentiment research for popular classification tasks. However, there has been little research regarding the relationship between the sentiment of images and its annotations from a multi-modal standpoint. In this demonstration, we built a tool to visualize psycholinguistic groundings for a sentiment dataset. For each image, individual psycholinguistic ratings are computed from the image's metadata. A sentiment-psycholinguistic spatial embedding is computed to show a clustering of images across different classes close to human perception. Our interactive browsing tool can visualize the data in various ways, highlighting different psycholinguistic groundings with heatmaps.

DOI： 10.3758/s13428-018-1099-3

More-Natural Mimetic Words Generation for Fine-Grained Gait Description International conference

Hirotaka Kato, Takatsugu Hirayama, Ichiro Ide, Keisuke Doman, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

Lecture Note in Computer Science 2020.1.4

Event date： 2020

Language：English Presentation type：Poster presentation

Venue：Deajeon Convention Center, Daejeon, Korea

A mimetic word is used to verbally express the manner of a phenomenon intuitively. The Japanese language is known to have a greater number of mimetic words in its vocabulary than most other languages. Especially, since human gaits are one of the most commonly represented behavior by mimetic words in the language, we consider that it should be suitable for labels of fine-grained gait recognition. In addition, Japanese mimetic words have a more decomposable structure than these in other languages such as English. So it is said that they have sound-symbolism and their phonemes are strongly related to the impressions of various phenomena. Thanks to this, native Japanese speakers can express their impressions on them briefly and intuitively using various mimetic words. Our previous work proposed a framework to convert the body-parts movements to an arbitrary mimetic word by a regression model. The framework introduced a phonetic space" based on sound-symbolism, and it enabled fine-grained gait description using the generated mimetic words consisting of an arbitrary combination of phonemes. However, this method did not consider the "naturalness" of the description. Thus, in this paper, we propose an improved mimetic word generation module considering its naturalness, and update the description framework. Here, we define the co-occurrence frequency of phonemes composing a mimetic word as the naturalness. To investigate the co-occurrence frequency, we collected many mimetic words through a subjective experiment. As a result of evaluation experiments, we confirmed that the proposed module could describe gaits with more natural mimetic words while maintaining the description accuracy."

DOI： 10.1007/978-3-030-37734-2_18

視覚特徴と言語特徴を用いた単語の心像性推定の検討

松平茅隼, カストナーマークアウレル, 井手一郎, 川西康友, 平山高嗣, 道満恵介, 出口大輔, 村瀬洋

言語処理学会第26回年次大会 2020.3.9

Modeling Eye-Gaze Behavior of Electric Wheelchair Drivers via Inverse Reinforcement Learning International conference

Yamato Maekawa, Naoki Akai, Takatsugu Hirayama, Luis Yoichi Morales, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

2020 IEEE International Conference on Intelligent Transportation Systems 2020.9.21

Event date： 2020

Language：English Presentation type：Oral presentation (general)

Venue：Rhodes, Greece (Virtual)

It is intuitively obvious that eye-gaze behaviors of experienced drivers are different from those of novice drivers. However, it is not easy to understand the difference in their behavior quantitatively. In this work, we present an explainable eye-gaze behavior modeling method for electric wheelchair drivers based on Inverse Reinforcement Learning (IRL). We first create feature maps that represent risk factors during driving. These feature maps are able to represent not only to what but also from where drivers pay attention. IRL uses the feature maps to learn the reward representing the eye-gaze behaviors and allows us to see important features via the automatic acquisition of the reward. Through analysis of the learned model, we show quantitative evidence that eye-gaze behaviors of experienced drivers are better-balanced by paying attention to multiple risks.

DOI： 10.1109/ITSC45102.2020.9294255

A study on a coloring method for document overviews

Chihaya Matsuhira, Marc Aurel Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2020.9.9

ソフト順序制約付きラベル境界緩和法に基づく列車前方映像のセマンティックセグメンテーション

振津勇紀, 出口大輔, 川西康友, 井手一郎, 村瀬洋

第23回画像の認識・理解シンポジウム(MIRU) 2020.8.5

移動する複数物体への群衆からの4次元注目度ヒートマップ生成の初期検討

武田一馬, 川西康友, 平山高嗣, 出口大輔, 井手一郎, 村瀬洋, 永野秀尚, 柏野邦夫

第23回画像の認識・理解シンポジウム（MIRU2020） 2020.8.5

複数画像系列の重み付き統合による自車位置推定

後藤優太, 久徳遙矢, 出口大輔, 川西康友, 井手一郎, 村瀬洋

第23回画像の認識・理解シンポジウム(MIRU) 2020.8.5

物体の同一性を評価する誤差関数の導入による姿勢・形状変化を独立に扱える GAN の提案

川西康友, 出口大輔, 井手一郎, 村瀬洋

第23回画像の認識・理解シンポジウム(MIRU) 2020.8.4

物体追跡を活用したCenterNetの弱教師あり学習

森太郎, 出口大輔, 川西康友, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2020.8.4

Performance Boost of Attribute-aware Semantic Segmentation via Data Augmentation for Driver Assistance International conference

Mahmud Dwi Sulistiyo, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Takatsugu Hirayama, Hiroshi Murase

The 8th IEEE International Conference on Information and Communication Technology 2020.6.24

Event date： 2020

Language：English Presentation type：Oral presentation (general)

This paper is an extension of our work in developing an attribute-aware semantic segmentation method which focuses on pedestrian understanding in a traffic scene. Recently, the trending topic of semantic segmentation has been expanded to be able to collaborate with the object’s attributes recognition task; Here, it refers to recognizing a pedestrian’s body orientation. The attribute-aware semantic segmentation can be more beneficial for driver assistance compared to the conventional semantic segmentation because it can provide a more informative output to the system. In this paper, we conduct a study of the data augmentation usage as an effort to enhance the performance of the attribute-aware semantic segmentation task. The experiments show that the proposed method in augmenting the training data is able to improve the model’s performance. We also demonstrate some of qualitative results and discuss the benefits to a driver assistance system.

DOI： 10.1109/ICoICT49345.2020.9166219

Preliminary Study on Attention Degree Estimation for Multiple Objects Based on Similarity between Gaze-Point and Gaze-Target Movements

Kazuma Takeda, Yasutomo Kawanishi, Takatsugu Hirayama, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hidehisa Nagano, Kunio Kashino

2020.5.15

On the quantification of the mental image of visual concepts for multi-modal applications

Marc Aurel Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Daisuke Deguchi, Hiroshi Murase

2020.5.7

Prediction of Pedestrians' Road Crossing at Intersection based on Estimation of Head Orientation

高木俊平, 梅村充一, 牛田勝憲, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

IEICE General Conference 2020.3.19

超低解像度FIR画像内での人物位置と動作の違いに着目した骨格推定法の検討

岩田紗希, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 相澤知禎

動的画像処理実利用化ワークショップ(DIA) 2020.3.10

Event date： 2020

Language：Japanese Presentation type：Oral presentation (general)

Venue：国立沖縄工業高等専門学校

近年，高齢化の進展により，独居高齢者に向けた見守りシステムが注目されている．しかし，見守りシステムにはプライバシーの問題が存在する．そこで我々はプライバシーの問題を軽減でき，さらに暗闇での撮影にも強い赤外線センサアレイを用いて撮影した超低解像度FIR画像系列から人物の骨格を推定する手法を提案してきた．本発表では特に超低解像度FIR画像内での人物位置と動作の違いに着目した骨格推定法について検討する．具体的には，超低解像度FIR画像内で人物位置に依存しない特徴を抽出するため，低解像度画像において影響が大きいと考えられる中間層でのPoolingをせずに，特徴抽出の最後にGlobalMaxPoolingを導入する．さらに動作の種類に合わせて，時系列情報と空間的情報を有効活用できるネットワークを提案する．実験では，赤外線センサアレイの画角内の様々な位置で人物を撮影したデータセットを用いて，従来手法と提案手法で特定の人物位置で学習を行ない，未学習位置で骨格推定精度を評価した．その結果，人物の動作を滑らかに推定でき，定量的にも精度が向上することを確認した．

車両の進路情報を条件とした cGAN による走路推定

右島琢也, 久徳遙矢, 出口大輔, 川西康友, 井手一郎, 村瀬洋

動的画像処理実利用化ワークショップ(DIA) 2020.3.10

Event date： 2020

Language：Japanese Presentation type：Poster presentation

Venue：国立沖縄工業高等専門学校

近年，自動運転に関する研究開発が活発になされており，限定された環境下ではあるものの公道での走行実験等も進められている．しかし，交差点は事故の危険性が高く，交差点を含む一般道を状況に応じて安全に走行するための課題は多い．このような背景から，車載カメラを用いて詳細に周囲環境を認識し，周囲の状況を考慮して安全に走行できる道路上の領域（走路）を推定する技術が求められている．そこで本発表では，車載カメラ画像と，目的地までの経路から得られる車両の進路情報を条件（Condition）とした，conditional GANの枠組みを利用して走行すべき走路を推定する手法を提案する．実走行データから構築したデータセットを用いた評価実験により，画像のみを入力とする比較手法に比べて，提案手法では走路推定精度が15.0%向上することを確認した．

Occlusion-Robust Pose-Feature Representation Learning for Object Pose Estimation from a Depth Image

Hiroki Tatemichi, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Ayako Amma

IEICE Technical Report (PRMU) 2019.12.20

On Visualizing Psycholinguistic Groundings for Sentiment Image Datasets

Marc Aurel Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Daisuke Deguchi, Hiroshi Murase

Meeting on Image Recognition & Understanding 2019.8.1

Event date： 2019

Language：English

Venue：グランキューブ大阪（大阪府立国際会議場）

Recent multimedia applications commonly use text and imagery from Social Media for tasks related to sentiment research. As such, there are various image datasets for sentiment research for popular classification tasks. However, there has been little research regarding the relationship between the sentiment of images and its annotations from a multi-modal standpoint. In this research, we built a tool to visualize psycholinguistic groundings for a sentiment dataset. For each image, individual psycholinguistic ratings are computed from the image's metadata. A sentiment-psycholinguistic spatial embedding is computed to show a clustering of images across different classes close to human perception. Our interactive browsing tool can visualize the data in various ways, highlighting different psycholinguistic groundings with heatmaps.

Viewpoint Recommendation for Object Pose Estimation via Pose Ambiguity Minimization

Nik Mohd Zarifie Hashim, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

The 22nd Meeting on Image Recognition and Understanding (MIRU) 2019.8.1

Event date： 2019

Language：English Presentation type：Poster presentation

Venue：Osaka International Convention Center

Recently, helper robots become popular in our social life, especially for helping the elderly and the disabled people to perform their daily tasks at home. To handling objects, object pose estimation from a depth image is an essential task of the helper robots. However, an object’s pose is often ambiguous from an observation from only a single viewpoint. If we can observe the object from additional viewpoints, the pose estimation result will be better. Thus, we propose a next viewpoint recommendation method based on pose ambiguity minimization. We confirmed and showed the proposed method outperformed other comparative methods on synthetic object images.

Visualization of group work via sensing of real world activities

Daisuke Deguchi

2019.6.26

Hand Orientation Estimation in Probability Density Form International conference

Kazuaki Kondo, Daisuke Deguchi, Atsushi Shimada

The Fourth International Workshop on Egocentric Perception, Interaction and Computing 2019.6.17

超低解像度遠赤外線画像からの人物骨格推定の検討

岩田紗希, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 相澤知禎

画像センシングシンポジウム(SSII) 2019.6.13

Event date： 2019

Language：Japanese Presentation type：Poster presentation

Venue：パシフィコ横浜アネックスホール

近年，高齢化社会の進展が問題となっており、高齢者の健康の暮らしのためには身体機能の維持が必須である．そのためには日常的に，身体の動きを把握する必要があるが，センサ装着が必要な方法や可視光カメラを用いる方法ではセンサの装着忘れやプライバシの問題がある．
そこで，超低解像度遠赤外線画像を用いた骨格推定法を提案する．現在，高解像度な可視光画像からの骨格推定は可能であるため，本手法では可視光カメラと赤外線カメラで同時に撮影をするシステムを構築し，学習データを収集する．それを用いて，ニューラルネットワークを学習し，超低解像度遠赤外線画像から直接骨格を推定する．

A Preliminary Study on Integrating Camera and LiDAR Pedestrian Detections Adaptive to Surrounding Environmental Conditions

Haruya Kyutoku, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Kazuki Kato, Hiroshi Murase

IEICE Technical Report (PRMU) 2019.5.30

A Study on Human Pose Estimation from an Extremely Low-Resolutiohn FIR image Sequence

Saki Iwata, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomoyoshi Aizawa

Japan-Taiwan Joint Workshop on Multimedia and HCI 2019.4.14

A Study on Occlusion-Robust Object Pose Estimation with a De-occluding AutoEncoder

Hiroki Tatemichi, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Ayako Amma

Japan-Taiwan Joint Workshop on Multimedia and HCI 2019.4.14

Estimating the Imageability of a sentence for image caption evaluation International conference

Kazuki Umemura, Marc Aurel Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

Japan-Taiwan Joint Workshop on Multimedia and HCI 2019.4.13

'KamiRepo' System with Automatic Student Identification to Handle Handwritten Assignments on LMS

Daisuke Deguchi

2019.3.25

時系列平滑化を用いた列車前方映像に対するセマンティックセグメンテーション手法の検討

振津勇紀, 新村文郷, 出口大輔, 川西康友, 井手一郎, 村瀬洋, 向嶋宏記, 長峯望

電子情報通信学会総合大会 2019.3.20

畳み込みの多段階分解によるSemantic Segmentationの高速化

野田紘司, 久徳遙矢, 川西康友, 出口大輔, 井手一郎, 村瀬洋

電子情報通信学会総合大会 2019.3.20

Event date： 2019

Language：Japanese Presentation type：Oral presentation (general)

Venue：早稲田大学西早稲田キャンパス

近年，Semantic Segmentationは自動運転や高度運転支援の要素技術として注目を集めている．しかし，高精度なSemantic Segmentation手法の計算コストは高く，実時間処理は困難である．従って，精度を維持したまま，より高速に計算する手法が求められている．Semantic Segmentationの処理は，畳み込み演算の計算時間が大部分を占める．提案手法では，XceptionモジュールのDepthwise convolutionを垂直・水平方向に分解することで畳み込み演算のさらなる高速化を試みる．実験により，mIoUの低下を抑えつつ，パラメータ数と実行時間を削減可能なことを確認した．

A Study on the Pose Estimation of an Occluded Object by a De-occluding AutoEncoder

Hiroki Tatemichi, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Ayako Amma

2019 IEICE General Conference 2019.3.20

Analyzing Changes of Eye Gaze Movements as Becoming Skilled at Driving an Electric Wheel Chair

Yamato Maekawa, Naoki Akai, Luis Yoichi Morales, Takatsugu Hirayama, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

2019 IEICE General Conference 2019.3.20

超低解像度遠赤外線画像からの人物姿勢推定の初期検討

岩田紗希, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 相澤知禎

情報処理学会全国大会 2019.3.15

Event date： 2019

Language：Japanese Presentation type：Oral presentation (general)

Venue：福岡大学七隈キャンパス

近年，高齢化社会の進展が問題となっており、高齢者の健康の暮らしのためには身体機能の維持が必須である．そのためには日常的に，身体の動きを把握する必要があるが，センサ装着が必要な方法や可視光カメラを用いる方法ではセンサの装着忘れやプライバシの問題がある．
そこで，超低解像度遠赤外線画像を用いた姿勢推定法を提案する．現在，高解像度な可視光画像からの骨格推定は可能であるため，本手法では可視光カメラと赤外線カメラで同時に撮影をするシステムを構築し，学習データを収集する．それを用いて，ニューラルネットワークを学習し，超低解像度遠赤外線画像から直接姿勢を推定する．

画像キャプションの質的評価に向けた文の心像性推定手法の検討

梅村和紀, カストナーマークアウレル, 井手一郎, 川西康友, 平山高嗣, 道満恵介, 出口大輔, 村瀬洋

言語処理学会年次大会 2019.3.14

A preliminary study on estimating word imageability labels using Web image data mining

Marc Aurel Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Daisuke Deguchi, Hiroshi Murase

2019.3.14

LIDARから得られる3D点群を用いた自転車認識

山本大貴, 新村文郷, 出口大輔, 川西康友, 井手一郎, 加藤一樹, 村瀬洋

動的画像処理実利用化ワークショップ(DIA) 2019.3.8

事例ベースの姿勢正規化による白杖利用者認識に向けた検討

西田尚樹, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 朴君

動的画像処理実利用化ワークショップ(DIA) 2019.3.7

Event date： 2019

Language：Japanese Presentation type：Poster presentation

Venue：北九州国際会議場

本研究では,視覚障害者を支援するために,人物の姿勢変化から歩行者系列が白杖利用者か否か分類す
ることを目的とする.しかし,人物の向きによって画像上の人物姿勢は大きく異なるため,分類しなければなら
ない姿勢パターンが多くなり,分類が困難となる.そこで本発表では,事例ベースで様々な向きの姿勢をある1つ
の向きの姿勢に正規化する手法を提案する.分類する姿勢のパターンが限定されることにより,高精度の分類が
可能となる.評価実験において,提案手法により認識率が 5% 向上することを確認した.

運転者による歩行者の見つけやすさ向上のためのヘッドライトシステム

前田高志, 平山高嗣, 川西康友, 出口大輔, 井手一郎, 村瀬洋

動的画像処理実利用化ワークショップ(DIA) 2019.3.7

Event date： 2019

Language：Japanese Presentation type：Oral presentation (general)

Venue：北九州国際会議場

夜間における歩行者の交通死亡事故が多発しており，その原因として運転者による歩行者の視認が困難であることが挙げられる．近年，通常の前方照射に加えて選択的照射が可能なヘッドライトが開発されており，その技術を活かして歩行者に選択的に光を照射することで歩行者の見つけやすさを向上させることが考えられる．我々はこれまでに点滅に着目して効果的な照射法を検討し，特定の周波数において点滅光の照射が効果的であることを確認しているが， 1 つの固定された周辺光条件しか想定していなかった．そこで本研究では，周辺光条件ごとに効果的な点滅照射を分析する．具体的には，運転環境を模擬した臨場感のある仮想環境において 6 種類の周辺光条件を設定し，通常のロービーム照射，ハイビーム照射および 7 種類の点滅周波数を用いて実験を行なった．実験結果から，点滅照射が見つけやすさ向上に有効であることや，異なる周辺光条件では効果的な周波数が異なることを確認した．

SNS投稿写真のVisual Conceptに基づく時空間類似地域マイニング

陳璐, 川西康友, 井手一郎, 平山高嗣, 道満恵介, 出口大輔, 村瀬洋

データ工学と情報マネジメントに関するフォーラム（DEIM） 2019.3.4

Event date： 2019

Language：Japanese Presentation type：Oral presentation (general)

Venue：ホテルオークラJRハウステンボス

旅行を計画する際，満足のいく計画を立てるためには，旅先の雰囲気を予め把握することが重要である．ある地域の訪問予定時の雰囲気が，既に知っている地域のある時期の雰囲気と似ていることが分かれば，その地域の訪問時の雰囲気を直感的に把握することできる．これを実現するため，我々は旅行者の体験を反映した大量のSNS投稿写真に着目した．具体的には，写真に付随する時空間情報を用いて写真をクラスタリングし「時期情報付き地域」を獲得し，写真のVisual Conceptに基づいて時空間類似地域をマイニングすることで，時期を考慮した類似地域の組を獲得する手法を提案する．手法の有用性を示すため，Flickr に投稿された写真を用いて時空間類似地域マイニング実験を行った．また，被験者実験を通して，提案手法の妥当性を確認した．

画像付き料理レシピの地域属性推定の検討

伊藤耀一朗, 道満恵介, 川西康友, 平山高嗣, 井手一郎, 出口大輔, 村瀬洋

データ工学と情報マネジメントに関するフォーラム（DEIM） 2019.3.4

Event date： 2019

Language：Japanese Presentation type：Oral presentation (general)

Venue：ホテルオークラJRハウステンボス

近年,投稿型料理レシピポータルサイトが普及している.ウェブ上には膨大な数の料理レシピが存在し,
掲載されている料理の種類は多岐にわたる.しかし,それに伴い,サイト利用者が検索の際に目的とする料理レシピ
件数を絞りこむことが難しくなりつつある.そこで本研究では,地域属性(スペイン料理,中華料理など)ごとに料
理の味や見た目が大きく異なることに着目し,料理レシピがもつ多様な情報から,機械学習を用いて作成される料理
の地域属性を推定する手法を提案する.学習には,料理の完成画像から得られた画像特徴,素材一覧から得られた素
材特徴,調理手順文の動詞から得られた手順特徴の 3 つを組み合わせて用いる.結果として,これら 3 つの全特徴を
用いた手法で 8 割近い推定精度が得られることを確認した.

Hard Negative Mining from in-Vehicle Camera Images based on Multiple Observations of Background Patterns International conference

Masashi Hontani, Haruya Kyutoku, David Robert Wong, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

International Conference on Computer Vision Theory and Applications (VISAPP) 2019 2019.2.26

Event date： 2019

Language：English Presentation type：Oral presentation (general)

Venue：Vienna House Diplomat Prague, Prague, Czech Republic

In recent years, the demand for highly accurate pedestrian detectors has increased due to the development of advanced driving support systems.
For the training of an accurate pedestrian detector, it is important to collect a large number of training samples.
To support this, this paper proposes a ``hard negative'' mining method to automatically extract background images which tend to be erroneously detected as pedestrians.
Negative samples are selected based on the assumption that frequent patterns observed multiple times in the same location are most likely parts of the background scene.
As a result of an evaluation using in-vehicle camera images captured along the same route, we confirmed that the proposed method can automatically collect false positive samples accurately.
We also confirmed that a highly accurate detector can be constructed using the additional negative samples.

Next Viewpoint Recommendation by Pose Ambiguity Minimization for Accurate Object Pose Estimation International conference

Nik Mohd Zarifie Hashim, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Ayako Amma, Norimasa Kobori

International Conference on Computer Vision Theory and Applications (VISAPP) 2019 2019.2.25

Event date： 2019

Language：English Presentation type：Oral presentation (general)

Venue：Vienna House Diplomat Prague, Prague, Czech Republic

3D object pose estimation by using a depth sensor is one of the important tasks in activities by robots. To reduce the pose ambiguity of an estimated object pose, several methods for multiple viewpoint pose estimation have been proposed. However, these methods need to select the viewpoints carefully to obtain better results. If the pose of the target object is ambiguous from the current observation, we could not decide where we should move the sensor to set as the next viewpoint. In this paper, we propose a best next viewpoint recommendation method by minimizing the pose ambiguity of the object by making use of the current pose estimation result as a latent variable. We evaluated viewpoints recommended by the proposed method and confirmed that it helps us to gain better pose estimation results than several comparative methods on a synthetic dataset.

Pedestrian Intensive Scanning for Active-scan LIDAR International conference

Taiki Yamamoto, Fumito Shinmura, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

International Conference on Computer Vision Theory and Applications (VISAPP) 2019 2019.2.25

Event date： 2019

Language：English Presentation type：Poster presentation

Venue：Vienna House Diplomat Prague, Prague, Czech Republic

In recent years, LIDAR is playing an important role as a sensor for understanding environments of a vehicle’s surroundings. Active-scan LIDAR is being actively developed as a LIDAR that can control the laser irradiation direction arbitrary and rapidly. In comparison with conventional uniform-scan LIDAR (e.g. Velodyne HDL-64e), Active-scan LIDAR enables us to densely scan even distant pedestrians. In addition, if appropriately controlled, this sensor has the potential to reduce unnecessary laser irradiations towards non-target objects. Although there are some preliminary studies on pedestrian scanning strategy for Active-scan LIDARs, in the best of our knowledge, an efficient method has not been realized yet. Therefore, this paper proposes a novel pedestrian scanning method based on orientation aware pedestrian likelihood estimation using the orientation-wise pedestrian’s shape models with local distribution of measured points. To evaluate the effectiveness of the proposed method, we conducted experiments by simulating Active-scan LIDAR using point-clouds from the KITTI dataset. Experimental results showed that the proposed method outperforms conventional methods.

電動車いす運転の熟達に伴う視行動変化の分析

前川大和, 赤井直紀, モラレスルイス洋一, 平山高嗣, 出口大輔, 川西康友, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2019.8.1

Event date： 2019

Language：Japanese Presentation type：Poster presentation

Venue：グランキューブ大阪（大阪府立国際会議場）

近年，先進国を中心に高齢化が進んでおり，電動車いすの需要が高まっている．しかし，電動車いすの利便性は高い一方で，事故が多発している．自動車の事故は視覚的な認知ミスが原因であることが多く，電動車いすも自動車と同様に運転者の視覚的な認知を支援することが事故防止に有効であると考えられる．また，熟練運転者と非熟練運転者の視行動に差異があることが知られており，熟練者の視行動に基づいて，運転者の視覚的な認知の支援をすることができると考えられる．本研究では，電動車いす運転における熟練者の視行動のモデル化を目指し，リスクが複数存在する箇所である死角あり狭路で運転する場合を想定して，熟達に伴う視行動の変化を3次元空間上で分析した．その結果，熟達するほど複数のリスクに対してバランスよく注意を払うことを確認した．

Class Augmentation For Semantic Segmentation by Integrating Multiple Methods

Wang Qishen, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2019.12.12

環境認識に関する基礎と最近の動向

出口大輔

日本機械学会東海支部講習会 2019.12.5

Scene-Adaptive Driving Area Prediction based on Automatic Label Acquisition from Driving Information International conference

Takuya Migishima, Haruya Kyutoku, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

5th IAPR Asian Conference on Pattern Recognition (ACPR2019) 2019.11.28

Semantic Segmentation of Railway Images Considering Temporal Continuity International conference

Yuki Furitsu, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase, Hiroki Mukoujima, Nozomi Nagamine

5th IAPR Asian Conference on Pattern Recognition (ACPR2019) 2019.11.27

An Analysis of How Driver Experience Affects Eye-Gaze Behavior for Robotic Wheelchair Operation International conference

Yamato Maekawa, Naoki Akai, Takatsugu Hirayama, Luis Yoichi Morales, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

2019 IEEE International Conference on Computer Vision (ICCV) Workshops 2019.11.2

Event date： 2019

Language：English Presentation type：Poster presentation

Venue：COEX Convention Center, Seoul, Korea

Drivers obtain information on surrounding environment using their eyesights. Experienced eye-gaze behavior is needed when driving at places where multiple risks exist to prepare for and avoid them. In this work, we analyze the change in eye-gaze behavior in such situations while a driver gains experience on the operation of a robotic wheelchair. Accurate distance information in the traffic environment is important to analyze the eye-gaze behavior. However, almost all previous works analyze eye-gaze behavior in a 2D environment, so they could not obtain accurate distance information. For this reason, we analyze eye-gaze behavior in 3D space. Concretely, we developed a novel eye-gaze behavior analysis platform based on a robotic wheelchair and estimated the driver's attention in 3D space. We try to analyze the eye-gaze behavior considering a useful field-of-view in 3D space based on the distance information instead of only the fixation point to investigate the objects that a driver implicitly pays attention to and from where s/he focuses on them. Results show that novice drivers pay attention to a single risk at a time. In contrast, they pay more attention to multiple risks simultaneously as they gain experience. Additionally, we discuss what features are effective to model the eye-gaze behavior based on the results.

DOI： 10.1109/ICCVW.2019.00545

Exemplar-based Pseudo-Viewpoint Rotation for White-Cane User Recognition from a 2D Human Pose Sequence International conference

Naoki Nishida, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Jun Piao

The 16-th IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS) 2019.9.20

Similar Seasonal-Geo-Region Mining based on Visual Concepts in Social Media Photos International conference

Yasutomo Kawanishi, Ichiro Ide, Chen Lu, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

5th IEEE Conference on Multimedia BigData 2019.9.11

A Preliminary Study on Pedestrian Abnormal Behavior Recognition based on Pose Heatmap from Surveillance Camera Images

Onur Temuroglu, Yasutomo Kawanishi, Daisuke Deguchi, Takatsugu Hirayama, Ichiro Ide, Hiroshi Murase, Mayuu Iwasaki, Atsushi Tsukada

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2019.9.10

A Preliminary Study on Pseudo-Viewpoint Conversion for White-Cane User Recognition from Arbitrary Viewpoints

Naoki Nishida, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Jun Piao

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2019.9.10

A Study on Human Skeleton Estimation from an Extremely Low-Resolution FIR Image Sequence for Monitoring Systems

Saki Iwata, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomoyoshi Aizawa

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2019.9.10

An Analysis of Simultaneous Image Matching on Various Datasets for Person Re-identification

Nik Mohd Zarifie Hashim, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2019.9.10

Event date： 2019

Language：English Presentation type：Oral presentation (general)

Venue：大同大学

Person re-identification is becoming a focus topic in many discussions recently. It becomes a vital role in public surveillance for identifying people across the street, inside supermarkets, and airports. Person re-identification aims to match person images captured at several non-overlapping camera views. For this reason, many advanced types of research had been competing to cope with the best solution for identifying multiple persons. Due to the redundant and mismatching which occurred in the traditional individual image matching scheme, the simultaneous image matching [1, 2] provides a solution which could avoid this downside. In this study, we analyze the performance of the simultaneous image matching on various datasets. We also evaluate a new image mask for feature extraction of SDALF.

Analysis of the Eye-gaze Behaviors of Robotic Wheelchair Drivers Considering the Geometric Relation with a Focused Object

Yamato Maekawa, Naoki Akai, Takatsugu Hirayama, Luis Yoichi Morales, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2019.9.10

CityWalks: An Extended Dataset for Attribute-aware Semantic Segmentation

Mahmud Dwi Sulistiyo, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Takatsugu Hirayama, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2019.9.9

Typicality analysis of a food within a food category based on its appearance

Masamu Nakamura, Yasutomo Kawanishi, Keisuke Doman, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2019.8.29

3つの学習特徴に基づく料理レシピの地域属性推定

伊藤耀一朗, 道満恵介, 川西康友, 平山高嗣, 井手一郎, 出口大輔, 村瀬洋

電子情報通信学会魅力工学研究会シンポジウム2019 2019.8.28

見えに基づく同一料理カテゴリの料理に関する典型度分析

中村真務, 川西康友, 道満恵介, 平山高嗣, 井手一郎, 出口大輔, 村瀬洋

電子情報通信学会魅力工学研究会シンポジウム2019 2019.8.28

欠損復元AutoEncoderによる遮蔽に頑健な物体姿勢推定の検討

立道大樹, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 安間絢子

画像の認識・理解シンポジウム(MIRU) 2019.8.1

Event date： 2019

Language：Japanese Presentation type：Poster presentation

Venue：グランキューブ大阪（大阪府立国際会議場）

近年，日常生活の支援のために家庭環境にロボットが導入されつつある．ロボットが物体を持ち運ぶためには，物体の姿勢を推定する必要があるが，物体が密集して存在する場合，他の物体に遮蔽されることで観測値に欠損が生じ，姿勢推定が困難である．欠損を復元するようにAutoEncoderを学習し，Encoder部分から得られる特徴ベクトルを姿勢推定に用いる手法があるが，この手法は欠損による物体中心の位置ずれを考慮していないため，欠損が大きいほど精度が低い．本発表では，欠損を復元できるように学習したAutoEncoderを，位置ずれの補正をしながら2回適用することで，観測値の欠損と位置ずれに対処した姿勢推定手法を提案する．また，パラメトリック固有空間法を拡張し，複数物体の姿勢変化からなる多様体上で姿勢補間することにより，同一クラスに属する未知形状の物体の未知姿勢であっても姿勢推定ができる手法を提案する．

走行履歴情報からの状況適応型走路の自動獲得

右島琢也, 久徳遙矢, 出口大輔, 川西康友, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2019.8.1

Event date： 2019

Language：Japanese Presentation type：Poster presentation

Venue：グランキューブ大阪（大阪府立国際会議場）

近年，自動運転技術が注目を集めており，その実現に向けた研究開発が盛んである．自動運転の実現のため，安全に走行可能な道路領域を推定する走路推定技術が求められている．走路の推定には周囲環境認識技術が不可欠であり，セマンティックセグメンテーションがその中で重要な役割を担うと期待されている．これまでに，セマンティックセグメンテーションを走路推定に用いる試みは行われているが，道路上に存在する他の車両や歩行者との接触は考慮されていない．我々は接触を回避した走路を得るために，車速の変化に着目して自車両の減速行動を学習し，複数フレームを用いて他物体の動きを学習することにした．本発表では，自車速を用いて車両の走行履歴情報を画像上に投影することで，多数のラベル画像を自動的に獲得し，他物体との接触がない走路（状況適応型走路）を推定する手法を提案する．名古屋駅周辺の走行履歴情報を用いて提案手法の評価を行なった結果，自動獲得した画像から走路推定器を構築できることを確認した．

Hand Emergence Features in Ego-centric View for Analyzing Cooperative Group Work

Kazuaki Kondo, Atsushi Shimada, Daisuke Deguchi

HCG Symposium 2018 2018.12.13

オノマトペによる歩容の記述の高精度化に向けたデータセットの構築

加藤大貴, 平山高嗣, 道満恵介, 川西康友, 井手一郎, 出口大輔, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2018.8.8

同一経路走行映像群からのネガティブサンプル自動抽出による人物検出器の高精度化

本谷真志, 久徳遙矢, 出口大輔, 川西康友, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2018.8.8

On Understanding Visual Relationships of Concepts by Visualizing Bag-of-Visual-Words Models

Marc Aurel Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Daisuke Deguchi, Hiroshi Murase

Meeting on Image Recognition & Understanding 2018.8.8

Event date： 2018

Language：English Presentation type：Poster presentation

Venue：札幌コンベンションセンター

Recent applications in image processing often use a multimodal approach using both text and imagery. This is prone to semantic gap issues when converting between image and language. There has been few research quantifiying visual differences when assessing semantic relationships. In this research, we analyze datasets composed of logically related concepts. By visualizing a Bag-of-Visual-Words (BoVW) model spatially, visual semantics of logically related sub-concepts are shown. To find hidden semantics of related concepts, the most common visual words of an image in relation to its neighbors are highlighted. This provides additional semantic knowledge on how sub-ordinate concepts visually relate to another. It is thought to give an insight on the human perception of these concepts, and can be used in future research to estimate psycholinguistic ratings.

Active Scan LIDARによる歩行者の向きを考慮した効率的な歩行者スキャン手法

山本大貴, 新村文郷, 出口大輔, 川西康友, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2018.8.7

Event date： 2018

Language：Japanese Presentation type：Poster presentation

Venue：札幌コンベンションセンター

近年，LASER 光の照射方向を瞬時かつ任意方向に制御可能な Active Scan LIDAR が開発中であり，局所的にスキャン密度を高めることにより遠距離の歩行者を検出可能になると期待されている．しかし，歩行者を効率的にスキャンする方法は実現されていない．そこで本発表では，歩行者の向き毎に構築した歩行者形状モデルと存在確率に基づいた歩行者尤度推定によるActive Scan LIDAR のための効率的な歩行者スキャン手法を提案する．

A Study on the Construction of a Traffic Signal Detector by Automatic Accumulation of Training Data Leveraging Driving Behavior Information

Takuya Migishima, Haruya Kyutoku, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2018 2018.9.3

姿勢を表現する多様体に基づくGANsを用いた特定クラス物体姿勢推定の検討

川西康友, 出口大輔, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2018.8.6

Event date： 2018

Language：Japanese Presentation type：Poster presentation

Venue：札幌コンベンションセンター

Generative Adversarial Nets（GANs）は，ある事前分布から画像などのデータを生成可能なネットワークであり，乱数から様々なデータを生成可能である．本研究では，物体の姿勢変化は潜在的には多様体で表現可能であることに着目し，多様体上に定義した確率分布から画像を生成するGANs の枠組みと，それを用いて学習画像を補間しつつ姿勢推定器を学習する手法を提案する．実験では，提案手法により，同一クラスに属する，学習データに含まれない物体の姿勢が補間できることを確認し，また，生成した画像を用いて姿勢推定器を学習することにより，高精度な姿勢推定ができることを示す．

車両周辺環境の違いに応じた歩行者検出信頼度の推定

久徳遙矢, 川西康友, 出口大輔, 井手一郎, 加藤一樹, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2018.8.6

Event date： 2018

Language：Japanese Presentation type：Poster presentation

Venue：札幌コンベンションセンター

車載カメラを用いた歩行者検出結果は，実環境下において依然として改善の余地がある．
そこで我々はこれまでに，ある検出器の出力に未検出や誤検出が含まれない可能性を，検出器の出力とは独立に検出器の信頼度として出力するシステムを提案してきた．
その中で，カメラから得た各画像の走行環境に応じた未検出と誤検出に関する信頼度について定義した．
本稿では，これらを入力画像から直接推定する信頼度推定器を構築し，実走行データを用いて推定精度を評価した

車載カメラを用いた自己位置推定と地図構築

出口大輔

第88回産研テクノサロン 2018.8.3

Event date： 2018

Language：Japanese Presentation type：Oral presentation (general)

Venue：大阪富国生命ビル

近年、自動運転車両や高度運転支援システムの研究開発が盛んであり、その中でも車載カメラを用いた周囲環境理解技術は大きな注目を集めている。自動運転等の応用を考えた場合、正確な自車位置の把握は欠くことのできない最も重要機能の一つである。本講演では、車載カメラを用いた自己位置推定に焦点を当て、車の特徴を活かした系列間照合によって位置推定を高精度に行う手法やそれらの地図構築への応用について紹介する。

Visualization of Real World Activity on Group Work International conference

Daisuke Deguchi, Kazuaki Kondo, Atsushi Shimada

20th International Conference on HCI International 2018 (HCII2018) 2018.7.20

Event date： 2018

Language：English Presentation type：Oral presentation (general)

Venue：Las Vegas, NV, USA

Group work is widely introduced and practiced as a method to achieve the learning goal efficiently by collaborating group members. However, since most types of group works are carried out in the real environment, it is very difficult to perform formative assessment and real time evaluation without students' feedbacks. Therefore, there is a strong demand to develop a method that supports evaluation of group work. To support evaluation of group work, this paper proposes a method to visualize the real world activity during group work by using first person view cameras and wearable sensors. Here, the proposed method visualizes three scores: (1) individual attention, (2) hand visibility, (3) individual activity. To evaluate the performance and analyze the relationships between scores, we conducted experiments of Marshmallow challenge" that is a collaborative work to construct a tower using marshmallow and spaghetti within a limit of time. Through the experiments, we confirmed that the proposed method has potential to become a evaluation tool for visualizing the activity of the group work."

DOI： 10.1007/978-3-319-91131-1_2

Estimating the attractiveness of a boxed lunch focusing on the attributes of side dishes

Masamu Nakamura, Keisuke Doman, Yasutomo Kawanishi, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

2018.6.8

フロントガラスへの映り込みが発生した際の歩行者視認性推定

森優介, 平山高嗣, 出口大輔, 川西康友, 井手一郎, 村瀬洋

パターン認識・メディア理解研究会(PRMU) 2018.5.18

Development of 'KamiRepo' System with Automatic Student Identification to Handle Handwritten Assignments on LMS International conference

Shunya Seiya, Ryuya Ito, Kosuke Okamoto, Ukyo Tanikawa, Shigeki Ohira, Daisuke Deguchi, Tomoki Toda

2018 the IEEE Global Engineering Education Conference (EDUCON2018) 2018.4.20

Event date： 2018

Language：English Presentation type：Oral presentation (general)

Venue：Santa Cruz de Tenerife, Canary Islands, Spain

A Learning Management System (LMS) has become a fundamental tool for higher education, and a framework to leverage digital education data in the LMS has attracted attention. On the other hand, there is strong demand to deal with various education data provided not only from electronic media but also non-electronic media, such as a handwritten assignment. To solve this problem, this paper describes the development of 'KamiRepo' system to make it possible to automatically upload handwritten assignments to the LMS. In this system, optical character recognition (OCR) is performed to identify scanned handwritten assignments of individual students and read their scores. Then, their scanned files automatically separated from the entire file of the scanned handwritten assignments are returned to the individual students through LMS together with their corresponding scores. Compared with a conventional system using the dedicated multifunction printer, our developed system is capable of 1) using general-purpose scanners, 2) using a user interface on Web browser, and 3) achieving accurate student identification. We have launched this system in our university in April 2017 and have evaluated its effectiveness. The experimental results using real data collected for 6 months showed that our system achieved 99.7% of success rate in the automatic upload process.

A Study on the Detection of Users of Whitecanes focusing on their Properties

Naoki Nishida, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Shoji Yachida

2018 IEICE General Conference 2018.3.22

A study on the automatic acquisition of training data for traffic signal detection based on labeling referring to driving information

Takuya Migishima, Haruya Kyutoku, Daisuke Deguchi, Yasutomo Kawanishi, Takatsugu Hirayama, Ichiro Ide, Hiroshi Murase

2018 IEICE General Conference 2018.3.22

A Preliminary Study on Estimating the Difficulty of Pedestrian Detection Adaptive to Vehicle Surrounding Environments Measured by LiDAR

Haruya Kyutoku, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Kazuki Kato, Hiroshi Murase

IEICE Technical Report (PRMU) 2018.3.18

Similar Geo-Region Mining based on Visual Concepts in Photos from Social Media

Hiroki Takimoto, Yasutomo Kawanishi, Ichiro Ide, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2018.3.9

ライトフィールド情報を活用した局所平面角度の推定とSIFT 特徴対応付けへの応用

清水政行, 川西康友, 出口大輔, 井手一郎, 村瀬洋

動的画像処理実利用化ワークショップ(DIA) 2018.3.8

Event date： 2018

Language：Japanese Presentation type：Oral presentation (general)

Venue：中京大学

近年，ライトフィールドカメラが一般に市販されるようになり，ライトフィールド情報を容易に取得する
ことが可能になった．ライトフィールド情報は空間中の光線情報を記録したものであり，撮影後の後処理によって任意の位置に合焦した画像を生成できるという特徴を有する．本発表では，このライトフィールド情報を活用することによって，画像中の任意の位置における最適な焦点距離と局所平面角度を同時に推定する手法を提案する．具体的には，ライトフィールドカメラの部分開口画像から算出されるSSD（Sum of Squared Difference）が合焦位置で最小になり，かつ，その隣接画素における最適な焦点距離が連続的に変化するというという2 つの性質に着目し，焦点距離と局所平面角度の同時推定手法を提案する．提案手法の有効性を確認するため，実環境において撮影した評価画像を用いて精度の検証を行った．その結果，テクスチャ情報が豊富な領域において良好な推定結果が得られることを確認した．

Improvement of taste estimation from a cooking recipe with an image

Yoichiro Ito, Keisuke Doman, Yasutomo Kawanishi, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2018.3.8

Study on the Improvement of Visibility by Projecting Flickering Light from Headlights

Takashi Maeda, Takatsugu Hirayama, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2018.3.8

フロントガラスへの映り込みを考慮した歩行者視認性推定

森優介, 出口大輔, 川西康友, 平山高嗣, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2018.3.2

Event date： 2018

Language：Japanese Presentation type：Oral presentation (general)

Venue：名古屋工業大学

車載カメラなどを用いた歩行者検出によって歩行者の存在を運転者に警告することで，認知誤りによる事故を減らすことができると期待される.しかし，検出した歩行者全てを運転者に警告することは，運転者の集中力低下や苛立ちの原因になる.
そのため，歩行者の視認性を推定し，視認が困難である歩行者のみを警告する方法が考えられる.
歩行者の視認性を推定する研究の多くは，入力として鮮明な車載カメラ画像を前提としているが，例えばダッシュボード上の物体がフロントガラスに映り込むことにより視野が妨害されることがある.このような視野への妨害は歩行者の視認性に悪影響を与えると考えられる.
そこで本研究では，フロントガラスへの映り込みを考慮した歩行者の視認性に着目し，その推定手法を提案する.

白杖固有の形状と存在範囲に着目した白杖利用者検出

西田尚樹, 出口大輔, 川西康友, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2018.3.2

Event date： 2018

Language：Japanese Presentation type：Oral presentation (general)

Venue：名古屋工業大学

駅などの危険な事故が起こりうる環境で白杖利用者を発見することは, 視覚障害者に対して人手の支援をするために重要である.
しかし, 入力画像全体を探索して検出を行なうと, 背景から白杖以外を誤検出する可能性があり, 精度の高い白杖検出は困難となる.
そこで我々は, 形状特徴を用いて白杖候補を検出した後，白杖が存在し得る範囲から白杖候補を絞り込むことで, 白杖を高精度に検出する手法を提案する.

運転者の運転行動情報を利用した信号機検出用学習データの収集

右島琢也, 出口大輔, 川西康友, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2018.3.2

Event date： 2018

Language：Japanese Presentation type：Oral presentation (general)

Venue：名古屋工業大学

交通死亡事故は交差点内で最も多く発生しており，交差点内の交通事故を防止するための有効な対策手段が求められている．
交差点での事故を防止するため，信号機中で点灯している信号灯の色（以下現示色と呼ぶ）に応じ，運転者に詳細な指示を与える運転補助技術が開発されている．
現示色までを含めて検出・認識する信号機検出器を構築する場合，色カテゴリ毎に位置ラベルを付与した多数の学習データを用意する必要がある．
しかし，学習データの獲得を人手で行なう場合，大きな労力が必要となる．
本研究では，信号機がある交差点を通過する際に，信号機の現示色によって運転挙動が異なることに着目することで，現示色を自動的に推定する手法を提案する．
具体的には，物体検出・追跡の技術を利用して位置ラベルを付与するとともに，運転行動情報を利用して色カテゴリを付与することで，自動的にアノテーションする手法を提案する．

Web画像の分布に基づく単語概念の視覚的な多様性の推定

カストナーマークアウレル, 井手一郎, 川西康友, 平山高嗣, 出口大輔, 村瀬洋

コンピュータビジョンとイメージメディア研究会(CVIM) 2018.3.1

Event date： 2018

Language：Japanese Presentation type：Oral presentation (general)

Venue：立命館大学

近年，画像処理の発展に伴い，自然言語と画像をつなぐ知識が必要になりつつある．概念辞書のようなデータベースは視覚性や画像特徴を考慮していないため，画像から自然な説明文を自動生成する際に障害になっている．そこで本発表では，単語概念の視覚的な多様性を推定する手法を提案する．提案手法では，まず，従来のデータセットに，Web画像の分布で測定した重みを使い，理想に近づくようにデータセットを再構成する．そしてMean-Shift法によって画像特徴のクラスタ数から視覚的な多様性を推定する．クラウドソーシングによる被験者実験を行い，決定した真値を用いた評価では，18語の名詞について従来のデータセットを用いた場合よりも正確に視覚性な多様性を推定できた．

Development of Kamirepo system for connecting paper-based assignments with LMS

Daisuke Deguchi

2018.2.28

A Preliminary Study on Optimizing Person Re-identification using Stable Marriage Algorithm International conference

Nik Mohd Zarifie Hashim, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

The International Workshop on Frontiers of Computer Vision (IW-FCV) 2018 2018.2.22

Event date： 2018

Language：English Presentation type：Oral presentation (general)

Venue：Future University Hakodate

Person re-identification gains an increasing interest
in the surveillance image processing field due to its’ importance
for security. Most approaches to solve the person re-identification
problem match persons one-by-one. However, redundant match-
ing where one of the person is selected for the matching pair
several times often occurs. It also degrades the overall image
matching performance. To overcome the issue, in this paper,
we propose a method which solves the person re-identification
problem for multiple persons simultaneously. Instead of one-
by-one matching, we consider person re-identification as an
instance of the Stable Marriage Problem (SMP). The result of an
experiment showed that the proposed method outperforms some
of the existing state-of-the-art methods applied to the VIPeR
dataset.

A study on wheelchair-users detection in a crowded scene by integrating multiple frames

Ukyo Tanikawa, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tatsuo Akiyama

IEICE Technical Report (PRMU) 2018.1.18

Efficient Pedestrian Scanning by Active Scan LIDAR International conference

Taiki Yamamoto, Fumito Shinmura, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

International Workshop on Advanced Image Technology (IWAIT) 2018 2018.1.8

Pedestrian Detection from Sparse Point-Cloud using 3DCNN International conference

Yoshiki Tatebe, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase, Utsushi Sakai

International Workshop on Advanced Image Technology (IWAIT) 2018 2018.1.8

地域・時期ごとのSNS投稿写真に基づく類似地域マイニング

陳璐, 川西康友, 井手一郎, 平山高嗣, 道満恵介, 出口大輔, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2018.8.7

Event date： 2018

Language：Japanese Presentation type：Poster presentation

Venue：札幌コンベンションセンター

知らない土地に旅行する際，その土地での旅行計画を円滑に進めるためには，行き先の地域別の雰囲気を理解することが重要である．ある地域が，既に知っている地域の雰囲気と似ていることが分かれば，その地域の雰囲気を直感的に把握できる．従来研究は，地域ごとのSNS 投稿写真を用いて地域間の類似性を計算することにより，雰囲気が似ている場所をマイニングしている．我々はこの研究を発展させ，各写真の撮影時期を考慮し，時期毎の類似地域をマイニングする手法を提案する．

Voting-based Hand-Waving Gesture Spotting from a Low-Resolution Far-Infrared Image Sequence International conference

Yasutomo Kawanishi, Chisato Toriyama, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomoyoshi Aizawa, Masato Kawade

2018 IEEE International Conference on Visual Communications and Image Processing (VCIP2018) 2018.12.11

Event date： 2018

Language：English Presentation type：Oral presentation (general)

Venue：永豐棧酒店臺中（臺中，臺灣）

We propose a temporal spotting method of a hand gesture from a low-resolution far-infrared image sequence captured by a far-infrared sensor array. The sensor array captures the spatial distribution of far-infrared intensity as a thermal image by detecting far-infrared waves emitted from heat sources. It is difficult to spot a hand gesture from a sequence of thermal images captured by the sensor due to its low-resolution, heavy noise, and varying duration of the gesture. Therefore, we introduce a voting-based approach to spot the gesture with template matching-based gesture recognition. We confirm the effectiveness of the proposed temporal spotting method in several settings.

DOI： 10.1109/VCIP.2018.8698650

Gaze-inspired Learning for Estimating the Attractiveness of a Food Photo International conference

Akinori Sato, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

20th IEEE Int. Symposium on Multimedia (ISM2018) 2018.12.10

Event date： 2018

Language：English Presentation type：Oral presentation (general)

Venue：臺中金典酒店（臺中，臺灣）

The number of food photos posted to the Web has been increasing. Most of the users prefer to post delicious-looking food photos. They, however, do not always look delicious. A previous work proposed a method for estimating the attractiveness of food photos, that is, the degree of how much a food photo looks delicious, as an assistive technology for taking a delicious-looking food photo. This method extracted image features from the entire food photo to evaluate the impression. In our work, we conduct a preference experiment where subjects are asked to compare a pair of food photos and measure their gaze. The proposed method extracts image features from local regions selected based on the gaze information and estimates the attractiveness of a food photo by learning regression parameters. Experimental results showed the effectiveness of extracting image features from outside the gaze regions rather than inside them.

DOI： 10.1109/ISM.2018.00015

Localizing the Gaze Target of a Crowd of People International conference

Yuki Kodama, Yasutomo Kawanishi, Takatsugu Hirayama, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hidehisa Nagano, Kunio Kashino

International Workshop on Attention/Intention Understanding 2018.12.3

Event date： 2018

Language：English Presentation type：Oral presentation (general)

Venue：Perth Convention and Exhibition Centre 21 Mounts Bay Rd Perth WA 6000 Australia

What target is focused on by many people?
Analysis of the target is a crucial task, especially in a cinema, a stadium, and so on.
However, it is very difficult to estimate the gaze of each person in a crowd accurately and simultaneously with existing image-based eye tracking methods, since the image resolution of each person becomes low when we capture the whole crowd with a distant camera.
Therefore, we introduce a new approach for localizing the gaze target focused on by a crowd of people.
The proposed framework aggregates the individually estimated results of each person's gaze.
It enables us to localize the target being focused on by them even though each person's gaze localization from a low-resolution image is inaccurate.
We analyze the effects of an aggregation method on the localization accuracy using images capturing a crowd of people in a tennis stadium under the assumption that all of the people are focusing on the same target, and also investigate the effect of the number of people involved in the aggregation on the localization accuracy.
As a result, the proposed method showed the ability to improve the localization accuracy as it is applied to a larger crowd of people.

Campus-wide Implementation of NU Kamirepo System for Handling Handwritten Assignments with an LMS

Daisuke Deguchi, Shunya Seiya, Shigeki Ohira, Tomoki Toda

2018.11.19

Analyzing Headlight Flicker Patterns for Improving the Pedestrian Detectability from a Driver International conference

Takashi Maeda, Takatsugu Hirayama, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2018 IEEE 21st International Conference on Intelligent Transportation Systems (ITSC2018) 2018.11.7

Event date： 2018

Language：English Presentation type：Oral presentation (general)

Venue：Maui, Hawaii, USA

In this paper, we analyze headlight flicker patterns which improve the pedestrian detectability from a driver. Recently, headlights are becoming capable of selectively projecting light on a pedestrian in addition to the normal forward projection. However, it is still not clear how the light should be
projected to effectively improve the visibility of the pedestrian. We actually analyze nine flicker patterns by controlling duty ratios and durations of lighting time, and conduct experiments in field and laboratory settings. As a result, we reveal that a specific fundamental frequency is effective for improving the pedestrian detectability from a driver. We also conclude that the difference between the two settings are not significant.

Attribute-aware Semantic Segmentation of Road Scenes for Understanding Pedestrian Orientations International conference

Mahmud Dwi Sulistiyo, Yasutomo Kawanishi, Daisuke Deguchi, Takatsugu Hirayama, Ichiro Ide, Jiang-Yu Zheng, Hiroshi Murase

2018 IEEE 21th International Conference on Intelligent Transportation Systems (ITSC2018) 2018.11.7

Event date： 2018

Language：English Presentation type：Oral presentation (general)

Venue：Maui, Hawaii, USA

Semantic segmentation is an interesting task for many deep learning researchers for scene understanding. However, recognizing details about objects’ attributes can be more informative and also helpful for a better scene understanding in intelligent vehicle use cases. This paper introduces a method for simultaneous semantic segmentation and pedestrian attributes recognition. A modified dataset built on top of the Cityscapes dataset is created by adding attribute classes corresponding to pedestrian orientation attributes. The proposed method extends the SegNet model and is trained by using both the original and the attribute-enriched datasets. Based on an experiment, the proposed attribute-aware semantic segmentation approach shows the ability to slightly improve the performance on the Cityscapes dataset, which is capable of expanding its classes in this case through additional data training.

Estimating the Scene-wise Reliability of LiDAR Pedestrian Detectors International conference

Haruya Kyutoku, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Kazuki Kato, Hiroshi Murase

2018 IEEE 21th International Conference on Intelligent Transportation Systems (ITSC2018) 2018.11.7

Event date： 2018

Language：English Presentation type：Oral presentation (general)

Venue：Maui, Hawaii, USA

Nowadays, development of driving support systems and autonomous driving systems have become active.
Pedestrian detection from in-vehicle sensors is one of the most important technologies for these systems.
However, outputs of pedestrian detectors can not be fully trusted in real environments.
Therefore, we propose an estimation system of pedestrian detector's reliabilities for a given scene.
This paper proposes a scene-wise reliability calculation method for LiDAR-based detectors, and a construction method for their estimators.
Here, the problem is how we can define the reliability.
The proposed method defines the reliability considering oversights as the strictest threshold without oversights.
Meanwhile, it defines the reliability considering false detections as the loosest threshold without false detections.
Experimental results showed that the proposed method could properly represent the reliability of a given scene, and estimate their reliability.

Estimation of Driver's Insight for Safe Passing based on Pedestrian Attributes International conference

Fumito Shinmura, Yasutomo Kawanishi, Daisuke Deguchi, Takatsugu Hirayama, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

2018 IEEE 21th International Conference on Intelligent Transportation Systems (ITSC2018) 2018.11.6

Event date： 2018

Language：English Presentation type：Oral presentation (general)

Venue：Maui, Hawaii, USA

In order to reduce traffic accidents between a vehicle and a pedestrian, recognition of a pedestrian who has a possibility of collision with a vehicle should be helpful. However, since a pedestrian may suddenly change his/her direction and cross the road, it is difficult to predict his/her behavior directly. Here, we focus on the fact that experienced drivers usually pass by a pedestrian while preparing to step on the brake at any moment when they feel danger. If driver assistant systems can estimate such experienced driver’s decisions, they could early detect the pedestrian in danger of collision. Therefore, we classify the driver’s decisions into three types by referring to the accelerator operation of drivers, and propose a method to estimate the type of the driver’s decision. The drivers are considered to decide their actions focusing on various behaviors and states of a pedestrian, namely pedestrian’s attributes. Since the driver’s decisions change along the timeline, the use of a temporal context is considered to be effective. Thus, in this paper, we propose an estimation method using a recurrent neural network architecture with the pedestrian’s attributes as input. We constructed a dataset collected by experienced drivers in control of the vehicle and evaluated the performance, and then confirmed the effectiveness of the use of pedestrian’s attributes.

自動運転車両の実現に向けた車載カメラによる環境理解

出口大輔

日本光学会年次学術講演会 2018.11.2

A Study on Similar Geo-region Mining based on Spatio-temporal Clustering of Social Media Photos

Chen Lu, Yasutomo Kawanishi, Ichiro Ide, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2018.10.26

Estimation of Driver's Behavior based on Pedestrian's Attributes when Passing by a Pedestrian

Fumito Shinmura, Yasutomo Kawanishi, Daisuke Deguchi, Takatsugu Hirayama, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

2018.10.17

Scene-wise Reliability Estimation of Pedestrian Detection using LiDAR

Haruya Kyutoku, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Kazuki Kato, Hiroshi Murase

2018.10.17

Epipolar geometry-based ego-localization using an in-vehicle monocular camera International conference

Haruya Kyutoku, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Workshop on Digital Signal Processing for In-Vehicle Systems 2018.10.8

Event date： 2018

Language：English Presentation type：Poster presentation

Venue：Nagoya University, Japan

Nowadays, development of driving support systems and autonomous driving systems have become active.
Vehicle ego-localization using in-vehicle sensors is one of the most important technologies for these systems.
Accordingly, various attempts to localize own vehicle from in-vehicle sensors have been made.
In general, the estimation accuracy of the traveling direction is lower than in the lateral direction.
Therefore, we propose a highly accurate method for ego-localization of the traveling direction based on epipolar geometry using an in-vehicle monocular camera.
The proposed method makes correspondences between in-vehicle camera images and database images with location information, and calculates the location using locations annotated to the corresponding database images.
However, there are many gaps due to the difference of speed and trajectory of vehicles even if the images are obtained along the same road.
To overcome this problem, the distance between the input image and the database image is calculated by the distance metric based on the epipolar geometry and the local feature method.
An experiment was conducted using actual images with correct locations, and we confirmed the effectiveness of the proposed method from its results.

Vehicle counting via car parts detection from an in-vehicle camera image International conference

Fumito Shinmura, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Workshop on Digital Signal Processing for In-Vehicle Systems 2018.10.8

Event date： 2018

Language：English Presentation type：Poster presentation

Venue：Nagoya University, Japan

This paper proposes a method to count vehicles from an in-vehicle camera image by regression based on car parts detection. In the case of an in-vehicle camera image, since vehicles are frequently occluded by other vehicles in traffic congestion, it is difficult to accurately count vehicles. Therefore, we propose a method to count vehicles by regression based on the number of visible car parts. For this, we make an estimator by learning the relation between the number of visible car parts and that of vehicles by Support Vector Regression. We evaluated our method using in-vehicle camera images recorded in an actual environment, where the proposed method performed better than counting detected vehicles.

HOYO: A Gait Dataset Annotated with Mimetic Words

Hirotaka Kato, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2018.9.7

地域・時期ごとのSNS投稿写真に基づく類似地域マイニング

陳璐, 川西康友, 井手一郎, 平山高嗣, 道満恵介, 出口大輔, 村瀬洋

電子情報通信学会魅力工学研究会シンポジウム 2018 2018.9.5

視線情報を利用した料理写真の魅力度推定手法

佐藤陽昇, 平山高嗣, 道満恵介, 川西康友, 井手一郎, 出口大輔, 村瀬洋

電子情報通信学会魅力工学研究会シンポジウム 2018 2018.9.5

A Study on the Detection of Users of White Cane Users focusing on Human Pose

Naoki Nishida, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Jun Piao

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2018 2018.9.4

Development of NU Server System to Link between Paper Report and LMS

Shunya Seiya, Ryuya Ito, Kosuke Okamoto, Ukyo Tanikawa, Shigeki Ohira, Daisuke Deguchi, Tomoki Toda

2017.12.15

A Study on Pedestrian Detection using Deep Learning for Low-Resolution LIDAR

Yoshiki Tatebe, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase, Utsushi Sakai

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2017 2017.9.8

A study on pedestrian detection by ACF using channnel statistics

Daisuke Deguchi, Haruya Kyutoku, Fumito Shinmura, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2017 2017.9.8

A study on recognition of Texting-While-Walking using the pose and the face orientation

Fumito Shinmura, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2017 2017.9.8

Negative samples extraction automatically from multiple image sequences captured on the same route for improving pedestrian detection

Masashi Hontani, Haruya Kyutoku, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2017 2017.9.8

Preliminary Study of Attribute-aware Semantic Segmentation for Pedestrian Understanding

Mahmud Dwi Sulistiyo, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2017 2017.9.8

A Preliminary Study on the Detection of Wheelchair Users using Faster R-CNN

Ukyo Tanikawa, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2017 2017.9.7

A Preliminary Study on Impression Description using Bi-directional RNN

Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2017 2017.9.8

Improvement of an attractiveness estimation method for food photos considering the appearance of main ingredients

Kazuma Takahashi, Keisuke Doman, Yasutomo Kawanishi, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2017.3.6

Active Scan LIDARを用いた歩行者検出のための効率的スキャン法

山本大貴, 出口大輔, 川西康友, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2017.3.3

Event date： 2017

Language：Japanese Presentation type：Oral presentation (general)

Venue：名古屋大学

遠方の歩行者においても局所的にスキャンの密度を高めることが可能なActive Scan LIDARが開発中である．
本研究では，歩行者の形状や存在確率を用いることで，Active Scan LIDARを用いた歩行者検出のための歩行者に対する効率的なスキャン法を提案する．

インテリジェントヘッドライトのための点滅光照射法の検討

前田高志, 平山高嗣, 川西康友, 出口大輔, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2017.3.3

Event date： 2017

Language：Japanese Presentation type：Oral presentation (general)

Venue：名古屋大学

運転者の歩行者視認を支援するために周辺の環境に応じて最適な光を照射する「インテリジェントヘッドライト」を提案する．その実現に向けて，点滅光照射法を検討し，有効な点滅パターンについて分析する．

人物検出器の高精度化に向けた走行映像群からのネガティブ学習サンプルの抽出手法

本谷真志, 出口大輔, 川西康友, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2017.3.3

Event date： 2017

Language：Japanese Presentation type：Oral presentation (general)

Venue：名古屋大学

歩行者検出器の高精度化において重要な要素である学習サンプルの質と量の改善に焦点を当て，
同じ経路を走行した複数の走行映像から歩行者検出器の学習に必要となるネガティブサンプルを自動抽出する手法を提案する．

撮影支援に向けた料理写真の魅力度推定手法の改良

佐藤陽昇, 平山高嗣, 川西康友, 出口大輔, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2017.3.3

Event date： 2017

Language：Japanese Presentation type：Oral presentation (general)

Venue：名古屋大学

本研究では，料理を魅力的に撮影するための支援を目的として，被験者に料理画像選好課題を課して視線情報を計測し，その分析に基づき設定した局所領域からの画像特徴抽出による料理写真の魅力度推定手法を提案した．

Deep Manifold Embedding for 3D Object Pose Estimation International conference

Hiroshi Ninomiya, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Norimasa Kobori, Yusuke Nakano

International Conference on Computer Vision Theory and Applications (VISAPP) 2017 2017.3.1

Can We Detect Pedestrians using Low-resolution LIDAR? International conference

Yoshiki Tatebe, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase, Utsushi Sakai

International Conference on Computer Vision Theory and Applications (VISAPP) 2017 2017.2.28

Wheelchair-user Detection Combined with Parts-based Tracking International conference

Ukyo Tanikawa, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Ryo Kawai

International Conference on Computer Vision Theory and Applications (VISAPP) 2017 2017.2.28

Can a Driver Assistance System Determine if a Driver is Perceiving a Pedestrian? International conference

Yuki Imaeda, Takatsugu Hirayama, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

International Conference on Computer Vision Theory and Applications (VISAPP) 2017 2017.2.27

A Study on Effective Frequency of Superposed Flickering Headlight for Improving Pedestrian Visibility

Takashi Maeda, Takatsugu Hirayama, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2017 2017.9.7

Automatic selection of Web contents towards automatic authoring of a video biography International conference

Ichiro Ide, Yasutomo Kawanishi, Kyoka Kunishiro, Frank Nack, Daisuke Deguchi, Hiroshi Murase

19th IEEE Int. Symposium on Multimedia (ISM2017) 2017.12.13

Migration of university-wide file sharing service using OSS

Takashi Matsuoka, Hisanori Tajima, Nanami Seki, Daisuke Deguchi, Hirokazu Hasegawa

2017.12.13

Survey on Attitudes towards Campus File Sharing Service

Hisanori Tajima, Takashi Matsuoka, Nanami Seki, Daisuke Deguchi, Hirokazu Hasegawa

2017.12.13

Summarization of news videos considering the consistency of auditory and visual contents International conference

Ichiro Ide, Ye Zhang, Ryunosuke Tanishige, Keisuke Doman, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

19th IEEE Int. Symposium on Multimedia (ISM2017) 2017.12.12

A Collaborative Report on The Open Apereo 2017 Conference

Yuji Tokiwa, Soichiro Fujii, Daisuke Deguchi, Shoji Kajita

IPSJ SIG Technical Report (CLE) 2017.12.9

A Study on Recognition of Pedestrian's Attribute using Pose Information

Fumito Shinmura, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

Vision Engineering Workshop (ViEW) 2017.12.8

車載カメラを用いた環境理解

出口大輔

経済情報学会主催セミナー 2017.12.6

Event date： 2017

Language：Japanese Presentation type：Oral presentation (general)

Venue：岐阜聖徳学園大学

近年，自動運転に関するニュースを報道で目にする機会が増え，その実現に対する期待も日に日に高まってきている．自動運転の実現には，車が今どこを走行しているかを正確に把握する技術が非常に重要となる．しかしながら，現在広く用いられているGPSのみでは，都市部等で十分な精度での位置計測ができないという問題がある．この問題の解決手段の一つとして，車載カメラを用いた自車位置推定技術が注目を集めている．そこで本講演では，カメラを用いた自車位置推定に焦点を当てるとともに，その関連技術についても紹介する．

Toward Describing Human Gaits by Onomatopoeias International conference

Hirotaka Kato, Takatsugu Hirayama, Yasutomo Kawanishi, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

2017 IEEE International Conference on Computer Vision (ICCV2017) Workshops 2017.10.28

Estimating the attractiveness of a food photo using a Convolutional Neural Network

Akinori Sato, Keisuke Doman, Takatsugu Hirayama, Ichiro Ide, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2017.10.20

Driver's Decision Analysis in Terms of Pedestrian Attributes -A Case Study in Passing by a Pedestrian- International conference

Fumito Shinmura, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

Workshop on Human Factors in Intelligent Vehicles 2017.10.16

Event date： 2017

Language：English Presentation type：Oral presentation (general)

Venue：Mielparque Yokohama, Kanagawa, Japan

In this paper, we report a case study on driver's decision in terms of pedestrian attributes. Among various traffic situations, the situation that a vehicle passes by a pedestrian is one of the major situations. To build a safety driving system that supports a non-experienced driver in such a situation, we analyzed how experienced drivers decide to handle the vehicle in such a situation. Since pedestrian’s behavior can be considered as a key factor for the decision, and also the behavior is different depending on their attributes," such as walking or stopping, noticing the vehicle or not, using a smartphone, etc., we analyzed what pedestrian's attributes affect the driver's decisions. For the analysis, we first built a large-scale dataset of driving data. Using the dataset, we clarified what attributes are dominant for the driver's decision."

A Study on GANs based on Pose Manifold for Rigid Object Pose Estimation

Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2017.10.13

Study on Gaze Target Localization from Low-Resolution Faces of Group of People

Yuki Kodama, Yasutomo Kawanishi, Takatsugu Hirayama, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hidehisa Nagano, Kunio Kashino

IEICE Technical Report (PRMU) 2017.10.13

A Preliminary Study on Reliability Estimation of Pedestrian Detectors

Haruya Kyutoku, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Kazuki Kato, Hiroshi Murase

2017.10.11

Analysis on the Relation between Pedestrian's Attributes and the Driver's Behavior when Passing by a Pedestrian

Fumito Shinmura, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

2017.10.11

Detection of Similar Geo-Regions based on Visual Concepts in Social Photos International conference

Hiroki Takimoto, Magali Philippe, Yasutomo Kawanishi, Ichiro Ide, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

Pacific-Rim Conference on Multimedia (PCM) 2017.9.28

Event date： 2017

Language：English Presentation type：Oral presentation (general)

Travel destination recommendation is useful to support travel.Considering the recommendation of regions within the destination area to visit, it could be difficult for the users to explicitly indicate their preference.Therefore, we considered that it would be more intuitive to recommend regions in the destination area that are similar to a region already well-known to the user.Thus, in this paper, we propose a method for the detection of similar geo-regions based on Visual Concepts in social photos.We report experimental results and analyses by applying the proposed method to the YFCC100M dataset.

視点に応じた魅力度が付与された料理画像データセット

井手一郎, 髙橋和馬, 道満恵介, 川西康友, 平山高嗣, 出口大輔, 村瀬洋

電子情報通信学会魅力工学研究会発足記念シンポジウム 2017.9.20

名古屋大学の事例紹介

出口大輔, 宮島千代美, 武田一哉

情報科学技術フォーラム(FIT) 2017.9.12

A Preliminary Study on Construction of a Reliability Estimator Adaptive to Vehicle Environments for Pedestrian Detectors

Haruya Kyutoku, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Kazuki Kato, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2017 2017.9.8

Automatic Selection of Web Contents Towards Automatic Authoring of a Video Biography

Kyoka Kunishiro, Frank Nack, Ichiro Ide, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2017.3.6

A Study on an Efficient Pedestrian Scanning Method by Active Scan LIDAR

Taiki Yamamoto, Fumito Shinmura, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2017 2017.9.7

A food image dataset tagged with attractiveness scores according to view-points (in Japanese)

Ichiro Ide, Kazuma Takahashi, Keisuke Doman, Yasutomo Kawanishi, Takatsugu Hirayama, Daisuke Deguchi, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2017 2017.9.7

An analysis on deep learning based action recognition from extremely low-resolution thermal image sequence

Takayuki Kawashima, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2017 2017.9.7

Improvement of an attractiveness estimation method of food photos by using gaze information during preference experiments

Akinori Sato, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2017 2017.9.7

Toward Zero-shot Gaits Translation by Onomatopoeia Based on the Relationship between Phoneme and Body-Parts Movement

Hirotaka Kato, Takatsugu Hirayama, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2017 2017.9.7

Action Recognition from Extremely Low-Resolution Thermal Image Sequence International conference

Takayuki Kawashima, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomoyoshi Aizawa, Masato Kawade

14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS2017) 2017.9.1

Event date： 2017

Language：English Presentation type：Poster presentation

Venue：Carlo V Castle, Lecce, Italy

This paper proposes a Deep Learning-based action recognition method from an extremely low-resolution thermal image sequence. The method recognizes daily actions by humans (e.g. walking, sitting down, standing up, etc.) and abnormal actions (e.g. falling down) without privacy concerns. While privacy concerns can be ignored, it is difficult to compute feature points and to obtain a clear edge of the human body from an extremely low-resolution thermal image. To address these problems, this paper proposes a Deep Learning-based action recognition method that combines convolution layers and an LSTM layer for learning spatio-temporal representation, whose inputs are the thermal images and their frame differences cropped by the gravity center of human regions. The effectiveness of the proposed method was confirmed through experiments.

DOI： 10.1109/AVSS.2017.8078497

Transifexを利用したコミュニティ翻訳

出口大輔

JTF 翻訳支援ツール説明会 2017.8.21

Estimation of the attractiveness of food photography focusing on main ingredients International conference

Kazuma Takahashi, Keisuke Doman, Yasutomo Kawanishi, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

9th Workshop on Cooking and Eating Activities (CEA2017) in conjunction with IJCAI2017 2017.8.20

Trajectory Ensemble: カメラネットワーク上での一時的な見えの変化に頑健な多人数追跡

川西康友, 出口大輔, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2017.8.10

車両周辺環境の違いに対する歩行者検出器の信頼度推定に関する初期検討

久徳遙矢, 川西康友, 出口大輔, 井手一郎, 加藤一樹, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2017.8.10

3DCNNを用いた低解像度点群からの歩行者検出

建部好輝, 出口大輔, 川西康友, 井手一郎, 村瀬洋, 酒井映

画像の認識・理解シンポジウム(MIRU) 2017.8.9

低解像度顔画像群からの集団の注目位置推定に向けて

児玉祐樹, 川西康友, 平山高嗣, 出口大輔, 井手一郎, 村瀬洋, 永野秀尚, 柏野邦夫

画像の認識・理解シンポジウム(MIRU) 2017.8.9

超低解像度温度画像系列を用いた家庭内人物行動認識に関する検討

川島昂之, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 相澤知禎, 川出雅人

画像の認識・理解シンポジウム(MIRU) 2017.8.9

医用画像処理からの巣立ち

出口大輔

第36回日本医用画像工学会大会（JAMIT2017） 2017.7.29

Event date： 2017

Language：Japanese Presentation type：Oral presentation (general)

本講演では，医用画像処理に軸足を置いた研究から私自身経験の無いITS研究分野に挑戦したこれまでの経験を紹介するとともに，そこで感じた研究分野を変えることの難しさ，新しいことへの挑戦の楽しさ，人との繋がりの大切さ，などについてまとめる．私自身は，名古屋大学工学部の4年生として鳥脇研究室の門をくぐり，博士号取得まで一貫して医用画像処理，特に気管支内視鏡ナビゲーションシステムの開発と関連するセグメンテーション技術の開発に取り組んできた．その後，縁あってコンピュータービジョン・パターン認識などの研究に軸足を移し，現在ではITSに関連する研究にも取り組んでいる．その間，研究分野を変えることの難しさや，新しいことに挑戦する楽しさを再認識することができた．特に，新しい人との繋がりは自身を大きく成長させてくれたと考えている．このような私自身のこれまでの経験が，今後新しい研究分野に挑戦する研究者の皆様の助けになれば幸いである．

Headgear Recognition by Decomposing Human Images in the Thermal Infrared Spectrum International conference

Brahmastro Kresnaraman, Yasutomo Kawanishi, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

15th International Conference on Quality in Research (QiR2017) 2017.7.26

Event date： 2017

Language：English Presentation type：Oral presentation (general)

Venue：Bali, Indonesia

Surveillance systems play a critical role in security and surveillance. A surveillance system with cameras that work in the visible spectrum is sufficient for most cases. However, problems may arise during the night, or in areas with less than ideal illumination conditions. Cameras with thermal infrared technology can be a better option in these situations since they do not rely on illumination to observe the environment. Furthermore, in our daily lives, it is common for humans to wear headgears such as glasses, masks, and hats. In surveillance, such headgears can be a hindrance to the identification of a person, and hence pose a certain degree of risk. This is not ideal in areas where the identity of a person is important, for example, in a bank. Therefore, in this paper we propose a headgear recognition method using an innovative decomposition approach on thermal infrared images. The decomposition method is based on Robust Principal Component Analysis, a modification of the popular Principal Component Analysis. The proposed method performs decomposition on a human image and isolates headgears in the image for recognition purposes. Experiments were conducted to evaluate the capability of the proposed method. The results show a positive outcome when compared with other methods.

DOI： 10.1109/QIR.2017.8168475

Trajectory Ensemble: Multiple Persons Consensus Tracking across Non-overlapping Multiple Cameras over Randomly Dropped Camera Networks International conference

Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

1st Workshop on Target Re-Identification and Multi-Target Multi-Camera Tracking 2017.7.21

Event date： 2017

Language：English Presentation type：Poster presentation

Venue：Hawaii Convention Center

Multiple person tracking over a camera network is usually performed by matching person images between adjacent cameras. It easily fails by a temporal appearance change of the persons caused by environmental illumination and observation orientation of a camera. To solve this problem, matching person images across not only adjacent cameras but also cameras multiple hops away in the camera network is effective, but such relaxation of spatiotemporal cues also cause tracking failure due to the increase of matching candidates. To avoid the failure, we introduce Random Camera Drop" to generate different camera networks which relax the spatio-temporal cues partially and randomly. We then, integrate tracking results over the networks to a consensus tracking result by a novel concept "Trajectory Ensemble", an extension of unsupervised ensemble learning for the multiple person tracking over a camera network problem. We evaluated the framework on several virtual datasets generated from a public dataset, "Shinpuhkan 2014 dataset" and confirmed that the proposed method achieves the highest tracking results among several comparative methods."

A study on keypoint matching with light field information

Masayuki Shimizu, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2017.6.23

Toward Description of Gaits by Onomatopoeia Based on the Relationship\\between Phoneme and Body-Parts Movement

Hirotaka Kato, Takatsugu Hirayama, Yasutomo Kawanishi, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (PRMU) 2017.6.22

Monocular Localization within Sparse Voxel Maps International conference

David Robert Wong, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2017 IEEE Intelligent Vehicles Symposium (IV2017) 2017.6.12

Event date： 2017

Language：English Presentation type：Poster presentation

Venue：Redondo Beach, California, USA

We introduce a method that uses a single camera to localize a vehicle within a pre-constructed map consisting of a voxel occupancy grid and road-line marker positions. Sophisticated mapping hardware is capable of creating high accuracy 3D maps of road environments, but localizing a vehicle within such maps is one of the challenges at the forefront of automated driving. A solution which is robust to dynamic environments, while using only inexpensive sensors, is a difficult problem. In addition, maps that enable precise localization consume a lot of data which is impractical for the expansive environments encountered in real-world road networks. We show how using the area of edge regions shared between rendered views of a compact voxel map and in-vehicle camera images can be coupled with non-linear optimization methods to determine the camera position and pose.

Active Scan LIDARを用いた歩行者検出のための効率的スキャン手法

山本大貴, 新村文郷, 出口大輔, 川西康友, 井手一郎, 村瀬洋

画像センシングシンポジウム(SSII) 2017.6.9

Event date： 2017

Language：Japanese Presentation type：Poster presentation

Venue：パシフィコ横浜アネックスホール

LIDAR は,対象までの距離や反射特性を測る環境認識センサであり,対象の 3 次元形状を分析できるため,これを用いた歩行者検出の研究が行われている.近年,LASER 光の照射方向を瞬時に制御可能な Active Scan LIDAR の開発が進められている.本研究では, Active Scan LIDAR を用いて歩行者から効率よく距離データを得るためのスキャン手法の開発を目的とする.
Active Scan LIDAR を用いた歩行者検出の実現に向けて,歩行者の形状による歩行者尤度推定,及び歩行者存在確率に基づく効率的なスキャン手法を提案する.
Active Scan LIDARを模擬した評価実験を行ったところ，全体を一定にスキャンする比較手法にくらべ，的中率，領域重なり率，歩行者抽出率すべての向上を確認でき，歩行者を効率的にスキャンできていることを確認した．

Sharing i18n Practices and Issues

Daisuke Deguchi, Soichiro Fujii, Shoji Kajita, Takahiro Sanada, Yuji Tokiwa

Open Apereo 2017 2017.6.7

Event date： 2017

Language：English Presentation type：Oral presentation (general)

Venue：Sheraton Society Hill Hotel in Philadelphia, PA

Apereo software are mostly developed in English-speaking countries. Therefore, users and developers rarely face issues caused by i18n and l10n. However, we, living in the non-English-speaking countries, are sometimes in trouble functionally caused by i18n and l10n. And we are continuously translating source code into our own language.

In this session, three topics will be presented.

At first, practices to apply IMS LTI and Caliper to existing tools on the Sakai based learning environment will be introduced. we are now encountering several issues caused by the lack of consideration of i18n in the specification. Points to solve these issues will be proposed.
Next, short stories will be shared to customize and localize Apereo tools to fit a typical usage of Japanese universities. Ideas to eliminate issues in the source codes fundamentally will be described.
Finally, a translation platform using a Web based translation support system such as Transifex will be explained in detail for those who will begin to translate Apereo software into your own language. In this platform, source code will be cloned from GitHub every night and one thing you should do is only to translate source code using Transifex.

ヘッドライトを用いた歩行者視認性向上のための点滅光照射パターンの検討

前田高志, 平山高嗣, 川西康友, 出口大輔, 井手一郎, 村瀬洋

コンピュータビジョンとイメージメディア研究会(CVIM) 2017.5.11

Event date： 2017

Language：Japanese Presentation type：Poster presentation

Venue：名古屋大学

薄暮時から夜間にかけての対歩行者死亡事故が多発しており，運転者の歩行者視認を支援するシステムへの需要が高まっている．我々はそのシステムとして，視認性が低い歩行者に周辺環境を考慮した最適な光を照射する「インテリジェントヘッドライト」を提案する．本研究ではその実現に向けて，点滅光照射法を検討した．具体的には，連続点灯時間およびデューティ比（1回の点滅における連続点灯時間の割合）を変化させたときの歩行者の視認性の違いを被験者実験により明らかにし，有効な点滅パターンについて分析した．その結果，瞬間的な照射かつ高速な点滅が効果的であり，2Hzの基本周波数を含む点滅において視認性が高くなる傾向が得られた．

料理写真の魅力度推定手法の改良

佐藤陽昇, 平山高嗣, 髙橋和馬, 道満恵介, 川西康友, 井手一郎, 出口大輔, 村瀬洋

コンピュータビジョンとイメージメディア研究会(CVIM) 2017.5.11

Event date： 2017

Language：Japanese Presentation type：Poster presentation

Venue：名古屋大学

近年，料理レシピサイトやSNSの普及によりWeb上への料理写真の投稿が増加している．Web上に投稿される料理写真は美味しそうに撮影されていることが望ましいが，その撮影は必ずしも容易ではない．従来研究では，料理を美味しそうに撮影するための支援技術として，料理写真の魅力度，つまり撮影された料理が美味しそうに見える度合いを推定する手法が提案されている．この手法では，魅力度付きの料理画像群から画像特徴を抽出し，回帰の枠組みにより任意の料理画像に対して魅力度を推定する．本研究では，閲覧者が一般的に注目する領域を分析し，それに基づいて画像特徴を抽出する領域を選択することにより，料理写真の魅力度推定手法を改良した．まず，画像の選好を評価する被験者実験を行い，魅力度を判断する際の視線情報を計測した．次に，視線の停留状態が続いた領域，すなわち注視領域を分析し，それに基づいて画像特徴の抽出領域を選択した．そして，画像全体から特徴抽出する従来手法と比較した結果から，注視領域外から特徴抽出することが有効であることが確認された．

人物検出器の高精度化に向けた走行映像群からのネガティブ学習サンプルの自動抽出に基づく人物検出器の追加学習

本谷真志, 久徳遙矢, 出口大輔, 川西康友, 井手一郎, 村瀬洋

画像センシングシンポジウム(SSII) 2017.5.9

Event date： 2017

Language：Japanese Presentation type：Poster presentation

Venue：パシフィコ横浜アネックスホール

近年,運転支援を目的とした車載カメラ映像からの人物検出技術が広く研究されている.一般に,検出器が誤って人物と判定した背景画像(ネガティブ学習サンプル)を追加学習することで,検出器の精度を改善できることが知られている.そこで本発表では,人物検出器の追加学習を行なうために,検出器が誤って人物と判定した背景画像をネガティブ学習サンプルとして自動抽出する手法を提案する.提案手法では,同一地点を長時間観測しても背景領域は大きく変化しないという性質を利用し,同一経路を走行した映像群を比較することでネガティブ学習サンプルを抽出する.そして,抽出したネガティブ学習サンプルを追加学習することにより,検出器の精度向上を図る.提案手法の有効性を確認するため,同一経路を 4 回走行して撮影した映像を用いて提案手法の評価を行なった.その結果,誤って人物を抽出することなくネガティブ学習サンプルの自動収集が可能であり,また得られたサンプルを用いた追加学習により精度が高い検出器を再構築できることを確認した.

A Preliminary Study on Gaze Target Localization from Low Resolution Faces of Group of People

Yuki Kodama, Yasutomo Kawanishi, Takatsugu Hirayama, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hidehisa Nagano, Kunio Kashino

2017 IEICE General Conference 2017.3.23

A Preliminary Study on Projection of Flickering Light on Pedestrian for Improving Detectability

Takashi Maeda, Takatsugu Hirayama, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2017 IEICE General Conference 2017.3.23

A Preliminary Study on an Efficient Scanning Method for Pedestrian Detection by Active Scan LIDAR

Taiki Yamamoto, Fumito Shinmura, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

2017 IEICE General Conference 2017.3.23

A preliminarily study on negative samples extraction from multiple image sequences captured on the same route

Masashi Hontani, Haruya Kyutoku, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

2017 IEICE General Conference 2017.3.23

名古屋大学における紙レポートシステムの試験導入と課題

戸田智基, 田上奈緒, 中務孝広, 松岡孝, 大平茂輝, 後藤明史, 出口大輔

Ja Sakai カンファレンス 2017.3.20

Proposal of a spectral random dots marker using local feature for posture estimation International conference

Norimasa Kobori, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEEE Virtual Reality 2017 2017.3.20

傘による遮蔽に頑健なパーツ参照型歩行者検出

新保祐人, 出口大輔, 川西康友, 井手一郎, 村瀬洋

動的画像処理実利用化ワークショップ(DIA) 2017.3.9

Event date： 2017

Language：Japanese Presentation type：Oral presentation (general)

Venue：島根県立産業交流会館　くにびきメッセ

近年，自動運転の実現に向けて自動車の周囲環境認識に関する研究が盛んに行なわれている．
その中でも，見落としが重大な事故につながる歩行者の検出は重要な課題である．しかし，傘を差した
歩行者は，傘によって頭部が遮蔽されるため検出が困難な対象として知られている．そこで本発表で
は，傘差し歩行者検出の高精度化を目的とし，パーツ参照型歩行者検出手法であるParts Driven Faster
RCNN を提案する．具体的には，Faster RCNN の候補領域抽出部において，傘と歩行者の関係性を学
習して傘の候補領域から歩行者の候補領域を推定することにより，頭部が遮蔽された歩行者でも候補領
域として抽出できるようにする．提案手法の有効性を確認するため，雨天時に撮影した車載カメラ画像
系列を用いて評価実験を行ない，傘差し歩行者に対して検出精度が向上することを確認した．

チャンネル特徴量を用いた歩行者検出技術

出口大輔

技術情報協会セミナー「歩行者検出における画像認識・LIDARの適用技術と自動運転への応用」 2017.1.11

Questionnaire survey for utilization of e-textbook in higher education

Daisuke Deguchi, Takaya Yamazato, Shigeki Ohira, Tomoki Toda, Hidehiro Nakajima, Katsusuke Shigeta, Yoshihiro Okada, Kazutsuna Yamaji

2016.12.15

A Preliminarily Study on Pedestrian Detectability Estimation Considering Visual Adaptation to Lighting Changes

Yuki Imaeda, Takatsugu Hirayama, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2016.10.21

Pedestrian Recognition for Proa ctive Driving Support System

Fumito Shinmura, Haruya Kyutoku, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Fukui, Yuji Yamauchi, Takayoshi Yamashita, Hironobu Fujiyoshi, Hiroshi Murase

2016.10.19

Recognition of Texting-While-Walking by Joint Features based on Arm and Head Poses International conference

Fumito Shinmura, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

2016.11.20

Event date： 2016

Language：English Presentation type：Oral presentation (general)

Venue：Taipei, Taiwan

Pedestrians texting-while-walking" increase the risk of traffic accidents, since they are often not paying attention to their surrounding environments and fails to notice approaching vehicles. Thus, the recognition of texting-while-walking from an in-vehicle camera should be helpful for safety driving assistance. In this paper, we propose a method to recognize a pedestrian texting-while-walking from in-vehicle camera images. The proposed approach focuses on the characteristic relationship between the arm and the head poses observed during a texting-while-walking behavior. In this paper, Pose-Dependent Joint HOG feature is proposed as a novel feature, which uses parts locations as prior knowledge and describes the cooccurrence of the arm and the head poses. To show the effectiveness of the proposed method, we constructed a dataset and evaluated it."

Obstacle detection with train frontal view camera

Hiroki Mukoujima, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Masato Ukai, Nozomi Nagamine, Ryuta Nakasone

19th Meeting on Image Recognition & Understanding (MIRU2016) 2016.8.3

A study on detection of pedestrians using umbrellas from an in-vehicle camera

Yuto Shimbo, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

19th Meeting on Image Recognition & Understanding (MIRU2016) 2016.8.2

A study on estimating the attractiveness of food images for photography assistance

Kazuma Takahashi, Keisuke Doman, Yasutomo Kawanishi, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

19th Meeting on Image Recognition & Understanding (MIRU2016) 2016.8.2

Image Selection Method with Object Recognition towards Automatic Authoring Of Video Obituary using Web Contents

Kyoka Kunishiro, Frank Nack, Ichiro Ide, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

19th Meeting on Image Recognition & Understanding (MIRU2016) 2016.8.2

Parts Selective DPM for detection of pedestrians possessing an umbrella International conference

Yuto Shimbo, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2016 IEEE Intelligent Vehicles Symposium (IV2016) 2016.6.19

Event date： 2016

Language：English Presentation type：Poster presentation

Venue：Gothenburg, Sweden

In recent years, pedestrian detection from an invehicle camera has been attracting attention.However, in the case of a raining situation, the detection accuracy decreases because the head of a pedestrian tends to be occluded by an umbrella. In oder to handle such cases, in this paper, as a variation of the Deformable Part Model (DPM) which is widely used in the field of object recognition, we propose Parts Selective DPM (PS-DPM)" which selectively chooses the original part filters and additional part filters trained independently. In the detection of pedestrians possessing an umbrella, the selection of head and umbrella parts will make pedestrian detection more robust to the occlusion. We conducted experiments to evaluate the performance of the proposed method. As a result, pedestrian detection with the proposed PS-DPM achieved high detection accuracy in rainy weather, compared with the detection by the conventional DPM. Moreover, we confirmed that it did not decrease the pedestrian detection accuracy in fine weather."

A Study on Activity Recognition based on Temporal Change of the Temperature Distribution obtained from a Far-Infrared Sensor Array

Takayuki Kawashima, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomoyoshi Aizawa, Masato Kawade

IEICE Technical Report (PRMU) 2016.6.14

A Study on the Detection of Wheelchair Users Combined with Parts Tracking

Ukyo Tanikawa, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Ryo Kawai, Toshikazu Sekiya

IEICE Technical Report (PRMU) 2016.6.14

Preliminary study on deep manifold embedding for 3D object pose estimation

Hiroshi Ninomiya, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Norimasa Kobori, Kunimatsu Hashimoto

IEICE Technical Report (PRMU) 2016.6.13

A Study on the Calculation of Geo-Regional Similarity based on the Contents of Social Photos

Hiroki Takimoto, Yasutomo Kawanishi, Ichiro Ide, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2016.6.2

Ja Sakai Panel Session

Daisuke Deguchi, Soichiro Fujii, Hisashi Hatakeyama, Shoji Kajita, Yuji Tokiwa

Open Apereo 2016 2016.5.25

Event date： 2016

Language：English Presentation type：Oral presentation (general)

Venue：New York University (Kimmel Centre for University Life)

Ja Sakai is a regional community of Apereo Foundation in Japan and coordinating activities in Japanese universities and affiliates. In addition to i18n contribution, several unique projects are carried on. In this panel session we will talk about the following; (1) Community translation using Transifex (2) LTI based presentation evaluation tool (3) Showcase of Sakai in universities (4) Learning analysis using IMS Caliper

人体部位の相対的位置関係を利用したオノマトペ歩容映像の識別に関する検討

加藤大貴, 平山高嗣, 川西康友, 道満恵介, 井手一郎, 出口大輔, 村瀬洋

コンピュータビジョンとイメージメディア研究会(CVIM) 2016.5.12

A study on estimating the attractiveness of food photography International conference

Kazuma Takahashi, Keisuke Doman, Yasutomo Kawanishi, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

2016 IEEE Second International Conference on Multimedia Big Data 2016.4.22

Event date： 2016

Language：English Presentation type：Oral presentation (general)

Venue：Taipei, Taiwan

This paper proposes a method for estimating the attractiveness of food photos in order to assist a user to shoot them attractively.
The proposed method extracts both color and shape features from input food images, and then integrates them according to a regression scheme.
By this way, the proposed method estimates the attractiveness of an unknown food photo.
We also created a food image dataset taken from various 3D-angles for each food category, and set target values of their attractiveness through subjective experiments.
Then, we evaluated the performance of the proposed method in two different ways of constructing the attractiveness estimator: One that constructs it for each food category, and the other that constructs a common attractiveness estimator for all food categories.
Experimental results showed the effectiveness of the proposed method in addition to the necessity for adaptively selecting the estimator depending on the appearance of foods for further performance improvement.

A Study on Activity Recognition based on Body Segmentation Using a Far-Infrared Sensor Array

Takayuki Kawashima, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2016 IEICE General Conference 2016.3.17

A Study on Deep Manifold Embedding for 3D Object Pose Estimation

Hiroshi Ninomiya, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Norimasa Kobori, Kunimatsu Hashimoto

2016 IEICE General Conference 2016.3.16

A Study on Specific Object Detection under Extreme Lighting Conditions by HDR Camera

Miho Komatsu, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2016 IEICE General Conference 2016.3.16

輝度の明滅が歩行者の見つけやすさに与える影響の初期検討

日比雅仁, 平山高嗣, 出口大輔, 川西康友, 井手一郎, 村瀬洋

電子情報通信学会総合大会 2016.3.15

A Study on the Detection of Wheelchair Users based on Parts Tracking

Ukyo Tanikawa, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2016 IEICE General Conference 2016.3.15

A classification method of cooking operations based on eye movement patterns International conference

Hiroya Inoue, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Ninth Biennial ACM Symposium on Eye Tracking Research and Applications (ETRA2016) 2016.3.15

A study on pedestrian detection using multiple frames obtained from a low resolution LIDAR

Yoshiki Tatebe, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase, Utsushi Sakai

2016 IEICE General Conference 2016.3.15

歩行者の姿勢に注目した「歩きスマホ」認識に関する検討

新村文郷, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 藤吉弘亘

動的画像処理実利用化ワークショップ(DIA) 2016.3.7

Event date： 2016

Language：Japanese Presentation type：Poster presentation

Venue：岩手大学

歩行者の「歩きスマホ」は周囲への注意が疎かになり，自動車の接近に気付きにくくなることから，交通事故に遭う危険性が高い．そのため，車載カメラを用いた歩行者の「歩きスマホ」の認識は，安全運転支援に有効だと考えられる．そこで本発表では，歩行者の「歩きスマホ」を認識する手法を提案する．具体的には，「歩きスマホ」中に見られる特徴的な歩行者の姿勢に注目し，腕と頭の位置の自演知識を用いることで腕と頭の姿勢の共起性を特徴として利用する認識手法を提案する．そして，実験を通して提案手法の有効性を示す．

誤検出マイニングに基づくシーン適応型歩行者検出の検討

鈴木悠暉, 出口大輔, 川西康友, 井手一郎, 村瀬洋

動的画像処理実利用化ワークショップ(DIA) 2016.3.7

Event date： 2016

Language：Japanese Presentation type：Oral presentation (general)

Venue：岩手大学上田キャンパス

近年，車載カメラ画像を用いた安全支援技術に関する研究が盛んに行われている．その中でも歩行者検出は重要な課題であり，様々な手法が提案されている．一般に，走行環境の見えが多様に変化し，それが原因で過検出が増加する．単一の検出器では，全ての走行環境の多様な見えに対応することは困難である．そこで，異なる走行環境下においても似たような誤検出が現れるという性質に着目することで，誤検出の低減を目指す．具体的には，誤検出の種類毎に学習画像をクラスタリングし，各クラスタに対して検出器を構築する．これらの検出器を組み合わせて歩行者検出を行うことにより検出精度向上を図る．提案手法の有効性を確認するために，公開データセットを用いて評価実験を行った．その結果，従来の手法による歩行者検出手法と比べ，提案手法によって検出精度が向上することを確認した．

高感度・高階調車載カメラ映像を用いた夜間歩行者検出のための予備検討

川西康友, 出口大輔, 井手一郎, 村瀬洋, 藤吉弘亘

動的画像処理実利用化ワークショップ(DIA) 2016.3.7

Event date： 2016

Language：Japanese Presentation type：Oral presentation (general)

自動運転や運転支援のために，車載カメラ映像からの歩行者検出技術の研究が盛んにおこなわれている．特に夜間は道路が暗いため，歩行者の検出が非常に困難である．本研究では，高感度・高階調カメラで観測した夜間の車載カメラ映像に対し，通常のカメラ向けに開発された歩行者検出法を適用するために，前処理としての輝度変換が有効であるかを検討した結果について報告する．

Study on an image selection method towards automatic authoring of video obituary using Web contents

Kyoka Kunishiro, Frank Nack, Ichiro Ide, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2016.3.7

Summarization of news videos based on the consistency of news text and image contents

Ye Zhang, Ryunosuke Tanishige, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2016.3.7

Deformable Part Modelsとパーツ追跡の統合による車椅子利用者の検出に関する検討

谷川右京, 川西康友, 出口大輔, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2016.3.4

オノマトペ表現に対応した歩容映像の識別に関する検討

加藤大貴, 平山高嗣, 川西康友, 出口大輔, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2016.3.4

地域別SNS投稿写真の画像内容に基づく特徴が類似する地域の検出に関する検討

滝本広樹, 川西康友, 出口大輔, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2016.3.4

複数フレーム特徴量を用いた低解像度LIDARによる歩行者検出

建部好輝, 出口大輔, 川西康友, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2016.3.4

赤外線センサアレイを用いた人物行動認識に関する検討

川島昂之, 川西康友, 出口大輔, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2016.3.4

輝度明滅による歩行者の強調が見つけやすさに与える影響の分析

日比雅仁, 平山高嗣, 出口大輔, 川西康友, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2016.3.4

高階調カメラ画像からの特定物体検出に関する検討

小松美穂, 川西康友, 出口大輔, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2016.3.4

HandWaving Gesture Detection Using a Far-Infrared Sensor Array with Thermo-Spatial Region of Interest International conference

Chisato Toriyama, Yasutomo Kawanishi, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomoyoshi Aizawa, Masato Kawade

International Conference on Computer Vision Theory and Applications (VISAPP) 2016 2016.2.29

Image transformation of eye areas for synthesizing eye-contacts in video conferencing International conference

Takuya Inoue, Tomokazu Takahashi, Takatsugu Hirayama, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takayuki Kurozumi, Kunio Kashino

International Conference on Computer Vision Theory and Applications (VISAPP) 2016 2016.2.29

Human Wearable Attribute Recognition using Decomposition of Thermal Infrared Images International conference

Brahmastro Kresnaraman, Yasutomo Kawanishi, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

22th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2016) 2016.2.19

Event date： 2016

Language：English Presentation type：Oral presentation (general)

Venue：Takayama, Gifu Prefecture

This paper addresses an attribute recognition problem in thermal images, specifically on worn objects such as hat and glasses. Although attribute recognition is a growing research field, there are not much work done in thermal infrared spectrum. In this spectrum, since illumination is not a problem, it could be a better option to be used in nighttime or poorly lit areas. The proposed method uses only the attribute information and excludes the unnecessary information for the recognition. To achieve this, we propose attribute recognition based on feature decomposition using Robust Principal Component Analysis (RPCA). An experiment to evaluate the capability of the proposed method was conducted on the dataset created for this research. The results show that the proposed method outperformed the method without decomposition by 14% in average with a maximum of 27% increase in a specific attribute.

Human Body Segmentation Using Texture Aware Grab-cut and Statistical Shape Models International conference

Esmaeil Pourjam, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

22th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2016) 2016.2.17

Event date： 2016

Language：English Presentation type：Oral presentation (general)

Venue：Takayama, Gifu Prefecture

Segmentation is one of active areas in computer vision field with application in many areas from entertainment to intelligent vehicles (IVs). Among the objects, humans themselves have always been among the most interested subjects because of
their special features. Since human body has an articulated structure, modeling and recognizing different variations in the body has proved to be very difficult. Wearing various kinds of clothes in different situations which can have a completely dissimilar appearance based on the clothing type, makes the modeling much more difficult. Add to this, the common problems of vision like illumination changes, blurring due to camera movements, etc. make the problem even more difficult. Thus having a system that can segment human subjects accurately can be useful in many applications. In this paper, we propose a system for segmenting human subjects using Statistical Shapes Models (SSM) feedback and a texture aware version of Grab-cut which incorporates texture feature for improving the segmentation accuracy. Our experiments show that the proposed system has an acceptable accuracy compared to the state-of-the art interactive methods and much better than the conventional ones.

A study on detection of a pedestrian holding an umbrella with a selective DPM

Yuto Shimbo, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2016.1.22

A method for gaze correction between video conference participants that synthesizes eye areas image within the perceptual range of eye contact

Takuya Inoue, Tomokazu Takahashi, Takatsugu Hirayama, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takayuki Kurozumi, Kunio Kashino

IEICE Technical Report (PRMU) 2016.1.21

Supervisory Driver Assistance System for Proactive Driving and Its Implementation

Yoshiki Ninomiya, Eijiro Takeuchi, Yamaguchi Takuma, Fumito Shinmura, Yuki Yoshihara, Yasuhiro Akagi, Yasutomo Kawanishi, Daisuke Deguchi, Soichiro Hayakawa, Tatsuya Suzuki, Hiroshi Murase, Shota Matsubayashi, Kazuhisa Miwa

2016.10.19

ファイル共有サービスの運用状況

松岡孝, 田島尚徳, 出口大輔, 森健策

大学ICT推進協議会（AXIES） 2016.12.14

Event date： 2016

Language：Japanese Presentation type：Oral presentation (general)

Venue：国立京都国際会館

近年，教育研究活動に関連する様々なデータを適切に管理することが強く求められている．この問題の解決を目指し，名古屋大学では教育研究に関わるデータの保存場所を組織的に整備する取り組みを行っている．平成27年4月より本運用を開始した本サービスの内容，システム構成，運用状況等について報告する．

Webコンテンツを用いた人物紹介映像の自動編集に向けて

國代京花, ナックフランク, 井手一郎, 川西康友, 出口大輔, 村瀬洋

HCGシンポジウム 2016.12.8

Relationship between Phonetic-Space and Body-Parts Movement for Description of Gaits by Onomatopoeia

Hirotaka Kato, Takatsugu Hirayama, Yasutomo Kawanishi, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

2016.12.7

Misclassification Tolerable Learning for Robust Pedestrian Orientation Classification International conference

Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

International Conference on Pattern Recognition (ICPR) 2016.12.5

Event date： 2016

Language：English Presentation type：Poster presentation

Venue：Cancun, Mexico

In this paper, we propose a multiclass classifier training method which reduces fatal" misclassifications by cost-relaxation of "tolerable" misclassifications in one-against-all classifiers training, named misclassification tolerable learning. In a binary classifier in the one-against-all classifiers, we introduce a new class group "conceptually similar classes," whose class labels are similar to the positive class. In the case of pedestrian orientation classification, the conceptually similar classes are defined as neighboring orientations to the positive orientation. We consider the misclassification of the conceptually similar classes to the positive class as tolerable misclassification. By relaxing the cost of the tolerable misclassifications, our proposed classification method reduces fatal misclassifications of non-similar classes. We evaluated the cost-relaxation effectiveness on several public datasets and confirmed that the proposed method outperforms the normal SVM on all of the datasets in the soft criterion by achieving 78.63% recognition rate on PDC Dataset."

致命的な誤認識を低減する多クラス分類器学習法による行動予測のための歩行者の向き認識

川西康友, 出口大輔, 井手一郎, 村瀬洋, 藤吉弘亘

画像の認識・理解シンポジウム(MIRU) 2016.8.3

エピポーラ幾何に基づく画像間距離と車載カメラ映像データベースを用いた詳細な自車位置推定

久徳遙矢, 川西康友, 出口大輔, 目加田慶人, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2016.8.4

Event date： 2016

Language：Japanese Presentation type：Poster presentation

Venue：アクトシティ浜松

本発表では，正面向き車載カメラで撮影した画像を入力とし，位置情報付き車載カメラ映像データベースとの比較により詳細な自車位置を推定する手法について報告する．
我々はこれまでに，フレーム対毎に算出するエピポーラ幾何に基づくフレーム間距離を用い，DPマッチングによりフレームの対応を求める手法を提案した．
また，このDPマッチングのための端点を高精度に与えるため，フレーム間距離の性質を用いた距離尺度の拡張を行なった．
これらの手法は，入力フレームと最も近い位置で撮影されたデータベース中のフレームを求めることを目的としている．
すなわち，算出可能な位置情報の精度は，車載カメラ映像データベースの撮影間隔に強く依存する．
そこでこれらの手法を拡張し，車載カメラ映像データベースの撮影間隔より詳細な位置情報を算出するための手法を提案する．
提案手法では，エピポーラ幾何に基づくフレーム間距離とカメラ間の距離が比例関係を持つ性質から，線形関数フィッティングによって自車位置を推定する．
実験から，データベースの撮影間隔の10倍詳細な位置情報を正解率80%で取得できることを確認した．

先読み運転支援のための車載カメラからの「歩きスマホ」認識に関する検討

新村文郷, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 藤吉弘亘

画像の認識・理解シンポジウム(MIRU) 2016.8.4

A study on deep manifold embedding for object pose estimation

Hiroshi Ninomiya, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Norimasa Kobori, Kunimatsu Hashimoto

19th Meeting on Image Recognition & Understanding (MIRU2016) 2016.8.4

A Preliminarily Study on Multi-Frames Features for LIDAR-Based Pedestrian Detection

Yoshiki Tatebe, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase, Utsushi Sakai

IEICE Technical Report (PRMU) 2016.9.5

Subjective Sensing of Real World Activity on Group Study International conference

Daisuke Deguchi, Kazuaki Kondo, Atsushi Shimada

18th International Conference on Collaboration Technologies (CollabTech2016) 2016.9.16

Event date： 2016

Language：English Presentation type：Poster presentation

Venue：しいのき迎賓館, 金沢市

Collaborative learning is efficient teaching/learning method, and it is widely introduced and practiced in various situations. However, it has a difficulty to perform formative assessment and real time evaluation without students' feedbacks. Therefore, demand for technologies to support formative assessment in collaborative learning is increasing. To tackle this problem, we have started the research project for automatic sensing and visualization of real world activities in collaborative learning. In this paper, we will report details about preliminary group work experiments and its results with visualization tool.

A Study for Applications of the Detection Method of Similar Geo-Regions based on Photographic Contents

Hiroki Takimoto, Yasutomo Kawanishi, Ichiro Ide, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2016.10.13

Accuracy improvement of food photo attractiveness estimation based on consideration of image features

Kazuma Takahashi, Keisuke Doman, Yasutomo Kawanishi, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2016.10.13

The proposal of encoding marker using local feature for posture estimation (in Japanese)

Norimasa Kobori, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (IE) 2016.10.6

Moving camera background-subtraction for obstacle detection on railway tracks International conference

Hiroki Mukoujima, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase, Masato Ukai, Nozomi Nagamine, Ryuta Nakasone

2016 IEEE International Conference on Image Processing (ICIP2016) 2016.9.25

Event date： 2016

Language：English Presentation type：Poster presentation

Venue：Phoenix, Arizona, USA

This paper proposes a method for detecting obstacles using train frontal view videos.
In recent years, obstacles detection using in-vehicle camera is actively developed for satisfying demands from various applications.
In the field of obstacle detection, most methods employ machine learning approach, and they can detect only trained obstacles, such as pedestrian, bicycle, etc.
Therefore, they cannot detect untrained general obstacles.
To overcome this problem, this paper propose a background subtraction method using moving camera.
The proposed method first computes frame-by-frame correspondences between the present and the database train frontal view image sequences, and detects obstacles by applying image subtraction to corresponding frames.
To confirm the effectiveness of the proposed method, experiments were conducted by using several image sequences captured at the experimental railroad track.
The experimental result showed that the proposed method could detect various obstacles accurately and effectively.

DOI： 10.1109/ICIP.2016.7533104

Pedestrian Attributes Recognition from an Image: A Survey

Yasutomo Kawanishi, Fumito Shinmura, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (PRMU) 2015.12.22

Taste and Texure Estimation of Food Based on Food Image and Ingredients List

Hiroki Matsunaga, Keisuke Doman, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2015.3.3

Toward understanding cooking activities based on gaze analysis

Hiroya Inoue, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2015.3.3

Typicality Analysis of the Combination of Ingredients in Cooking Recipes

Satoshi Yokoi, Keisuke Doman, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2015.3.3

A Study on Human Tracking using a Far-Infrared Sensor Array and a Thermo-Spatial Sensitive Histogram

Takashi Hosono, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomoyoshi Aizawa, Masato Kawade

IEICE Technical Report (PRMU) 2015.1.23

A study on detection of the type of a baggage utilizing multiple-viewpoints human images

Yasuhiro Asai, Kento Nishibori, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2015.1.23

A study on hand waving gesture recognition by thermo-spatial restriction using a far-infrared sensor array

Chisato Toriyama, Takashi Hosono, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2015.1.22

Cooking Operation Classification Based on Analysis of Eye Movement Patterns

Hiroya Inoue, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

2015.12.16

Summarization of multiple news videos based on term scores using responses of SNS users

Kosuke Kato, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2015.3.3

Distant Pedestrian Detection from an in-Vehicle Camera based on Observations of Forward Vehicles

Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

18th Meeting on Image Recognition & Understanding (MIRU2015) 2015.7.30

運転者から見た歩行者の危険度推定のための「歩きスマホ」認識

新村文郷, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 藤吉弘亘

画像の認識・理解シンポジウム(MIRU) 2015.7.29

A study on analyzing eye movements toward understanding cooking activities

Hiroya Inoue, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

18th Meeting on Image Recognition & Understanding (MIRU2015) 2015.7.29

Hand waving gesture classification using a far-infrared sensor array with Thermo-Spatial Region of Interest

Chisato Toriyama, Takashi Hosono, Yasutomo Kawanishi, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomoyoshi Aizawa, Masato Kawade

18th Meeting on Image Recognition & Understanding (MIRU2015) 2015.7.29

Image transformation of eye area for synthesizing eye-contacts in video conferencing

Takuya Inoue, Tomokazu Takahashi, Takatsugu Hirayama, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takayuki Kurozumi, Kunio Kashino

18th Meeting on Image Recognition & Understanding (MIRU2015) 2015.7.29

Typicality analysis of the combination of ingredients in a cooking recipe for assisting the arrangement of ingredients International conference

Satoshi Yokoi, Keisuke Doman, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

2015 IEEE International Conference on Multimedia and Expo (ICME2012) 2015.7.3

Event date： 2015

Language：English Presentation type：Oral presentation (general)

Venue：Torino, Italy

As the number of cooking recipes posted on the Web increases, it becomes difficult to find a cooking recipe that a user needs. Moreover, even if it can be done, it is still difficult for users to arrange the cooking recipe, for example, by replacing ingredients with different ones. To deal with such problems, we propose a framework for typicality analysis of the combination of ngredients. The framework calculates a typicality value for each combination of ingredients. The list of ingredients can be arranged by adjusting the typicality value by adding or removing ingredients iteratively. The effectiveness of the proposed framework was confirmed through subjective experiments.

Pedestrian Orientation Classification Utilizing Single-Chip Coaxial RGB-ToF Camera International conference

Fumito Shinmura, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

Workshop on Environment Perception for Automated On-road Vehicles in conjunction with 2015 IEEE Intelligent Vehicles Symposium (IV2015) 2015.6.28

Event date： 2015

Language：English Presentation type：Oral presentation (general)

Venue：Seoul, Korea

This paper proposes a method for pedestrian orientation classification. In image recognition, the accuracy is often degraded by the influence of background. In addition, it is also difficult to remove the background and extract only the human body from an image. To overcome these problems, we utilize a single-chip RGB-ToF camera. This camera can acquire RGB and depth images along the same optical axis at the same moment, and thus segmentation of the RGB image becomes easier by using the coaxial depth image. Our proposed method segmented a human body from its background accurately, which lead to the improvement of the accuracy of pedestrian orientation classification.

Pedestrian's Inattention Estimation based on Recognition of Texting While Walking from In-Vehicle Camera Images

Fumito Shinmura, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

IEICE Technical Report (PRMU) 2015.6.18

A study on analyzing the attractiveness of food photos using image features

Kazuma Takahashi, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

2015.6.11

A study on selecting scenes that match the news contents for news video summarization

Ye Zhang, Ryunosuke Tanishige, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2015.6.9

Translating Apereo Software: A Case Study using Sakai and Transifex International conference

Yuji Tokiwa, Daisuke Deguchi, Juan Jose Merono Sanchez, Jose Mariano Lujan Gonzalez, Diego del Blanco Orobitg

Open Apereo 2015 2015.6.3

Event date： 2015

Language：English Presentation type：Oral presentation (general)

Venue：Baltimore, Maryland, USA

Web based translation support systems such as Crowdin and Transifex make it easy for regional Sakai communities to collaborate globally in translation. In the fall and winter of 2014, Spanish Sakai community and Japanese Sakai community are collaborating in translation of Sakai 10 using Transifex as a common translation platform. This collaboration brought a lot of things to two communities. For instance, to develop a tool to import resource bundle files to Transifex in a specific manner, we can have an ease of use platform to translate modular designed software such as Sakai. And this platform will be extended for every regional community and for every project in Apereo community.
During this session we will talk about followings;
(1) Overview
(2) Benefits for Apereo community
(3) Context dependent translation by gettext Portable Object
(4) Community translation strategy in Sakai Spanish Users (S2U)
(5) Automatized process by Jenkins

A Study on Removal of Temporal Objects from Image Sequences Based on Adaptive Background Selection

Toru Kotsuka, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2015.3.20

A study on construction of pedestrian detectors adaptive to driving environment referring to false detection tendency

Yuki Suzuki, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2015.3.20

A study on the predicition of driver's pedestrian detectability considering characteristics of human fields-of-view while driving

Ryunosuke Tanishige, Keisuke Doman, Daisuke Deguchi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2015.3.20

Adaptive Reference Image Selection for Temporal Object Removal from Frontal In-vehicle Camera Image Sequences International conference

Toru Kotsuka, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

International Conference on Computer Vision Theory and Applications (VISAPP) 2015 2015.3.14

Event date： 2015

Language：English Presentation type：Oral presentation (general)

Venue：Berlin

In recent years, image inpainting is widely used to remove undesired objects from an image. Especially, the removal of temporal objects, such as pedestrians and vehicles, in street-view databases such as Google Street View has many applications in Intelligent Transportation Systems (ITS). To remove temporal objects, Uchiyama et al. proposed a method that combined multiple image sequences captured along the same route. However, when spatial alignment inside an image group does not work well, the quality of the output image of this method is often affected. For example, large temporal objects existing in only one image create regions that do not correspond to other images in the group, and the image created from aligned images becomes distorted. One solution to this problem is to select adaptively the reference image containing only small temporal objects for spatial alignment. Therefore, this paper proposes a method to remove temporal objects by integration of multiple image sequences with an adaptive reference image selection mechanism.

DOI： 10.5220/0005357102330239

A Preliminary Study on Human Attribute Classification in Thermal Image

Brahmastro Kresnaraman, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

2015 IEICE General Conference 2015.3.12

A Preliminary Study on the Construction of Pedestrian Detectors Referring to False Positive Tendency

Yuki Suzuki, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2015 IEICE General Conference 2015.3.12

A Study on Frame Alignment between Present and Past Train Frontal View Videos

Hiroki Mukoujima, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Masato Ukai, Nozomi Nagamine

2015 IEICE General Conference 2015.3.12

A Study on the Detection of Pedestrians holding an Umbrella based on Generative Learning

Yuto Shimbo, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2015 IEICE General Conference 2015.3.12

Estimation of Human Orientation using Coaxial RGB-Depth Images International conference

Fumito Shinmura, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

International Conference on Computer Vision Theory and Applications (VISAPP) 2015 2015.3.12

Event date： 2015

Language：English Presentation type：Oral presentation (general)

Venue：Berlin

Estimation of human orientation contributes to improving the accuracy of human behavior recognition. However,
estimation of human orientation is a challenging task because of the variable appearance of the human
body. The wide variety of poses, sizes and clothes combined with a complicated background degrades the
estimation accuracy. Therefore, we propose a method for estimating human orientation using coaxial RGBDepth
images. This paper proposes Depth Weighted Histogram of Oriented Gradients (DWHOG) feature
calculated from RGB and depth images. By using a depth image, the outline of a human body and the texture
of a background can be easily distinguished. In the proposed method, a region having a large depth gradient
is given a large weight. Therefore, features at the outline of the human body are enhanced, allowing robust
estimation even with complex backgrounds. In order to combine RGB and depth images, we utilize a newly
available single-chip RGB-ToF camera, which can capture both RGB and depth images taken along the same
optical axis. We experimentally confirmed that the proposed method can estimate human orientation robustly
to complex backgrounds, compared to a method using conventional HOG features.

DOI： 10.5220/0005305301130120

A preliminary Study on the Effect of a Secondary Task while Driving on Pedestrian Detectability

Yuki Imaeda, Ryunosuke Tanishige, Takatsugu Hirayama, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2015 IEICE General Conference 2015.3.11

傘と歩行者の位置関係を考慮した生成型学習法による傘差し歩行者検出

新保祐人, 出口大輔, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2015.3.9

撮影角度による見えの違いに注目した料理写真の魅力度分析

髙橋和馬, 村瀬洋, 井手一郎, 出口大輔

電子情報通信学会東海支部卒業研究発表会 2015.3.9

現在と過去の列車前方映像間のフレーム対応付けによる走行位置推定

向嶋宏記, 村瀬洋, 井手一郎, 出口大輔

電子情報通信学会東海支部卒業研究発表会 2015.3.9

運転時のサブタスクを考慮した歩行者の見落としやすさ推定

今枝祐綺, 平山高嗣, 出口大輔, 井手一郎, 村瀬洋

電子情報通信学会東海支部卒業研究発表会 2015.3.9

Introduction of video streaming service linked with Sakai at Nagoya University

Akifumi Goto, Yoshihiro Ohta, Takahiro Nakatsukasa, Nao Tanoue, Shigeki Ohira, Daisuke Deguchi, Kensaku Mori

Ja Sakai Annual Conference 2015 2015.3.9

Detectors ensemble based on false positive mining for pedestrian detection

Yuki Suzuki, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

18th Meeting on Image Recognition & Understanding (MIRU2015) 2015.7.30

Position Interpolation using Feature Point Scale for Decimeter Visual Localization International conference

David Robert Wong, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2015 IEEE International Conference on Computer Vision (ICCV2015) Workshops 2015.12.12

Event date： 2015

Language：English Presentation type：Oral presentation (general)

Venue：Santiago, Chile

Vehicle ego-localization is a critical task not only for in-car navigation systems, but also for emerging intelligent and autonomous vehicle technologies. Visual localization methods that determine current location by performing image matching against a pre-constructed database have an accuracy limited by the spatial distance between database images. In this paper we propose a method that uses the scale of feature points to interpolate the position of the query image between two database images. We show how this simple contribution offers an appreciable improvement in localization accuracy with an extremely minimal increase in processing time, especially when used in conjunction with image matching methods that already monitor feature scale. Our experiments showed an increase of up to 33\% in average localization accuracy when compared to a method without any interpolation.

A Collaborative Report on The Open Apereo 2015 Conference

Soichiro Fujii, Yuji Tokiwa, Daisuke Deguchi, Shoji Kajita

IPSJ SIG Technical Report (CLE) 2015.12.6

列車前方映像を用いた時空間差分による障害物検出に関する検討

向嶋宏記, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 鵜飼正人, 長峯望, 中曽根隆太

ビジョン技術の実利用ワークショップ(ViEW) 2015.12.3

情報サービスの安定運用と迅速な障害対応を目的とした機器情報管理データベースの構築

川田良文, 出口大輔, 渥美紀寿, 加藤芳秀, 嶋田創, 荻野正雄, 小川泰弘, 大野誠寛, 服部昌祐, 山田一成

大学ICT推進協議会（AXIES） 2015.12.3

Event date： 2015

Language：Japanese Presentation type：Poster presentation

Venue：ウインクあいち

名古屋大学情報連携統括本部では、学内向けに種々の情報サービスを提供している。昨今、サービスの多様化に伴って発生するシステムのトラブルの複雑化が大きな問題となっている。そこで、情報サービスに必要なリソースを可視化し、サービスの安定運用と迅速な障害対応を行う取り組みを行っている。昨年度は、機器情報管理データベースの構築に加え、機器情報とサービスを関連付ける機能の実装を行った。本発表では、機器情報管理データベースの機能と運用方法について報告する。

赤外線センサアレイを用いた温度と空間の絞り込みによる手振り動作検出

鳥山千智, 川西康友, 高橋友和, 出口大輔, 井手一郎, 村瀬洋, 相澤知禎, 川出雅人

ビジョン技術の実利用ワークショップ(ViEW) 2015.12.3

Detector Ensemble based on False Positive Mining for Pedestrian Detection International conference

Yuki Suzuki, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

3rd IAPR Asian Conference on Pattern Recognition (ACPR2015) 2015.11.6

Generation of a video summary on a news topic based on SNS responses to news stories International conference

Kosuke Kato, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

Proc. 4th Int Workshop on Crowdsourcing for Multimedia (CrowdMM'15) in conjunction with ACMMM2015 2015.10.30

A study on estimating the attractiveness of food photography composition

Kazuma Takahashi, Keisuke Doman, Yasutomo Kawanishi, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2015.10.8

終端フリーDPを用いた列車前方映像の照合による走行位置推定に関する検討

向嶋宏記, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 鵜飼正人, 長峯望, 中曽根隆太

電気・電子・情報関係学会東海支部連合大会 2015.9.29

A study on pedestrian detection in raining condition considering the positional relationship of an umbrella and a pedestrian

Yuto Shimbo, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2015 2015.9.29

Distant Pedestrian Re-Detection from an in-Vehicle Camera based on Detections by Other Vehicles International conference

Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

2015 IEEE Conference on Intelligent Transportation Systems (ITSC2015) 2015.9.16

Event date： 2015

Language：English Presentation type：Oral presentation (general)

Venue：Las Plmas de Gran Canaria, Spain

In this paper, we propose the re-detection paradigm, which is a detection with prior knowledge of the detection targets, and we introduce an implementation of the re-detection for distant pedestrian detection from an in-vehicle camera. We focus on the fact that other vehicles including forward vehicles can observe and detect pedestrians before the own vehicle observes them. Since appearances of pedestrians do not significantly change even though their locations are different, sharing images of the detected pedestrians among the vehicles, the own vehicle can use them as prior knowledge for detecting them again. Results of applying the proposed method to a dataset obtained by an in-vehicle camera demonstrate that the accuracy of pedestrian detection results can be significantly increased if prior knowledge of the pedestrians could be obtained.

DOI： 10.1109/ITSC.2015.200

Tastes and textures estimation of foods based on the analysis of its ingredients list and image International conference

Hiroki Matsunaga, Keisuke Doman, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

1st International Workshop on Multimedia Assisted Dietary Management 2015.9.8

Event date： 2015

Language：English Presentation type：Oral presentation (general)

Venue：Genova, Italy

Recently, the number of cooking recipes on the Web is increasing.
However, it is difficult to search them by tastes or textures although
they are actually important considering the nature of the contents.
Therefore, we propose a method for estimating the tastes and the
textures of a cooking recipe by analyzing them.
Concretely, the proposed method refers to an ingredients feature from
the ``ingredients list'' and image features from the ``food image'' in
a cooking recipe.
We confirmed the effectiveness of the proposed method through an
experiment.

Road scene understanding by using in-vehicle camera

Daisuke Deguchi

2015.9.3

ownCloudを用いた全教職員向けファイル共有サービスの構築

松岡孝, 田島尚徳, 出口大輔, 森健策

大学ICT推進協議会（AXIES） 2014.12.12

Single Camera Vehicle Localization Using SURF Scale and Dynamic Time Warping International conference

David Robert Wong, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2014 the IEEE Intelligent Vehicles Symposium (IV2014) 2014.6.10

Event date： 2014

Language：English Presentation type：Poster presentation

Venue：Dearborn, Michigan, USA

Vehicle ego-localization is an essential process for many driver assistance and autonomous driving systems. The traditional solution of GPS localization is often unreliable in urban environments where tall buildings can cause shadowing of the satellite signal and multipath propagation. Typical visual feature based localization methods rely on calculation of the fundamental matrix which can be unstable when the baseline is small.
In this paper we propose a novel method which uses the scale of matched SURF image features and Dynamic Time Warping to perform stable localization. By comparing SURF feature scales between input images and a pre-constructed database, stable localization is achieved without the need to calculate the fundamental matrix. In addition, 3D information is added to the database feature points in order to perform lateral localization, and therefore lane recognition.
From experimental data captured from real traffic environments, we show how the proposed system can provide high localization accuracy relative to an image database, and can also perform lateral localization to recognize the vehicle's current lane.

Estimation of Traffic Sign Visibility Considering Local and Global Features in a Driving Environment International conference

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Utsushi Sakai

2014 IEEE Intelligent Vehicles Symposium (IV2014) 2014.6.9

Event date： 2014

Language：English Presentation type：Poster presentation

Venue：Dearborn, Michigan, USA

This paper proposes a camera-based visibility estimation method for a traffic sign.
The visibility here indicates how a visual target is easy to be detected and recognized by a human driver (not a machine).
This research aims at realizing a nuisance-free driver assistance system which sorts out information depending on the visibility of a visual target, in order to prevent driver distraction.
Our previous study on estimating the visibility of a traffic sign considered only the effect of the local region around a target, assuming the situation that a driver's gaze is around it.
The proposed method integrates both the local features and global features in a driving environment without such an assumption.
The global features evaluate the positional relationships between traffic signs and the appearance around the fixation point of a driver's gaze, which considers the effect of the driver's entire field of view.
Experimental results showed the effectiveness of incorporating the global features for estimating the visibility of a traffic sign.

Estimation of a politician's stance based on his/her posts to microblogs

Hiromichi Iwai, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

2014.5.12

Estimation of the Representative Story Transition in a Chronological Semantic Structure of News Topics International conference

Kosuke Kato, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

4th International Conference on Multimedia Retrieval (ICMR2014) 2014.4.4

Event date： 2014

Language：English Presentation type：Poster presentation

Venue：Glasgow University

It is important to track the flow of topics to thoroughly understand the contents. Accordingly, a method that structures the chronological semantic relations between news stories, namely a 'topic thread structure' has been proposed.It allows the comprehensive understanding of a topic by chronologically tracking stories one by one from the initial story. However, this task imposes a user to watch many stories when it contains various sub-topics. Thus, we propose method that estimates the representative story transition in a topic thread structure. In the proposed method, features obtained from a story and those from the topic thread structure are used for the estimation. We confirmed the effectiveness of the proposed method by comparing the results obtained from the proposed method to the ground truth obtained from votes in a subjective experiment. However, this task imposes a user to watch many stories when it contains various sub-topics. Thus, we propose method that estimates the representative story transition in a topic thread structure. In the proposed method, features obtained from a story and those from the topic thread structure are used for the estimation. We confirmed the effectiveness of the proposed method by comparing the results obtained from the proposed method to the ground truth obtained from votes in a subjective experiment

A Preliminary Study on the Removal of Moving Objects in a Frontal In-vehicle Camera Image Sequence

Toru Kotsuka, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2014 IEICE General Conference 2014.3.20

A preliminary study on eye images synthesis for eye gaze correction for teleconferencing

Takuya Inoue, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2014 IEICE General Conference 2014.3.20

A preliminary study on pedestrian detection using a low resolution LIDAR

Yoshinori Ichikawa, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Utsushi Sakai, Hideaki Misawa

2014 IEICE General Conference 2014.3.20

A study on gesture detection by an infrared sensor array considering active areas

Chisato Toriyama, Takashi Hosono, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2014 IEICE General Conference 2014.3.20

Investigation on the Estimation of the Number of Vehicles in an In-Vehicle Camera Image based on Car Parts Detection

Fumito Shinmura, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2014 IEICE General Conference 2014.3.20

A Feasibility Study of Human Cloud Sensing

Atsushi Shimada, Daisuke Deguchi, Kazuaki Kondo, Takuya Funatomi

2014 IEICE General Conference 2014.3.18

Accuracy improvement of pedestrian detection from in-vehicle camera images based on environment adaptation using location information

Daichi Suzuo, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hiroyuki Ishida, Yoshiko Kojima

IEICE Technical Report (PRMU) 2014.3.13

Proposal of the weighted voting type co-training method for the construction of an accurate traffic sign detector

Yuji Kojima, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2014.3.13

名古屋大学におけるSakaiの利用状況およびリーディング大学院の活用事例の紹介

中務孝広, 太田芳博, 田上奈緒, 大平茂輝, 後藤明史, 出口大輔, 森健策

Ja Sakai カンファレンス 2014.3.10

Event date： 2014

Language：Japanese Presentation type：Oral presentation (general)

Venue：名古屋大学

名古屋大学では，2010年度からSakaiによるNUCT（Nagoya University Collaboration and course Tools）を，講義における利用を主たる目的として全学向けに運用してきた．本稿では，Sakaiにおける利用状況等について報告するとともに，博士課程教育リーディングプログラムにおける教育学習支援システムとして，Sakaiを利活用した事例について紹介する．

A method to relate news stories to Web news articles for video structuring using SNS

Kosuke Kato, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2014.3.7

Scene Duplicate Detection from News Videos by Sub-Region-based Motion Matching of a Face

Haruka Kumagai, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2014.3.7

A Study on the Estimation of Tastes of Cooking Recipes Based on Training Using Comments on Cooking Recipes as Supervisory Signals

Hiroki Matsunaga, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2014.3.6

A study on memory-based regression for spatial people density estimation

Yoshimune Tabuchi, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takayuki Kurozumi, Kunio Kashino

IEICE Technical Report (PRMU) 2014.2.13

Proposal of Human Cloud Sensing

Atsushi Shimada, Daisuke Deguchi, Kazuaki Kondo, Takuya Funatomi

IEICE Technical Report (PRMU) 2014.2.13

The 1st Feasibility Study toward Human Cloud Sensing

Daisuke Deguchi, Kazuaki Kondo, Takuya Funatomi, Atsushi Shimada

IEICE Technical Report (PRMU) 2014.2.13

The 2nd Feasibility Study toward Human Cloud Sensing

Kazuaki Kondo, Takuya Funatomi, Atsushi Shimada, Daisuke Deguchi

IEICE Technical Report (PRMU) 2014.2.13

Can a Human be a Sensor? International conference

Atsushi Shimada, Daisuke Deguchi, Kazuaki Kondo, Takuya Funatomi

20th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2014) 2014.2.5

Event date： 2014

Language：English Presentation type：Poster presentation

Venue：Okinawa National College of Technology

This paper discusses a novel sensing strategy to retrieve real-world information. Instead of using sensor devices such as cameras, microphones and so on, the proposed approach involves people in real-world sensing to acquire requested information as accurately and quickly as possible. We call the proposed sensing strategy as Human Cloud Sensing (HCS)". In this paper, we introduce the concept of HCS and report some experimental results which were conducted to investigate the feasibility of "Can a human be a sensor?"."

Environment adaptive pedestrian detection using in-vehicle camera and GPS International conference

Daichi Suzuo, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hiroyuki Ishida, Yoshiko Kojima

International Conference on Computer Vision Theory and Applications (VISAPP) 2014 2014.1.7

Event date： 2014

Language：English Presentation type：Oral presentation (general)

Venue：Lisbon

In recent years, accurate pedestrian detection from in-vehicle camera images is focused to develop a safety driving assistance system. Currently, successful methods are based on statistical learning. However, in such methods, it is necessary to prepare a large amount of training images. Thus, the decrease in the number of training images degrades the detection accuracy. That is, in driving environments with few or no training images, it is difficult to detect pedestrians accurately. Therefore, we propose an approach that collects training images automatically to build classifiers for various driving environments. This is expected to realize highly accurate pedestrian detection by using an appropriate classifier corresponding to the current location. The proposed method consists of three steps; Classification of driving scenes, collection of non-pedestrian images and training of classifiers for each scene class, and associating a scene-class-specific classifier with GPS location information. Through experiments, we confirmed the effectiveness of the method compared to baseline methods.

DOI： 10.5220/0004677003540361

Exemplar-Based Human Body Super-Resolution for Surveillance Camera Systems International conference

Kento Nishibori, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

International Conference on Computer Vision Theory and Applications (VISAPP) 2014 2014.1.6

Event date： 2014

Language：English Presentation type：Poster presentation

Venue：Lisbon

In this paper, we propose an exemplar-based super-resolution method applied to a human body in a surveillance video. Since persons are usually captured as low-resolution images by a video surveillance system, it is sometimes necessary to perform detection and identification of persons from not only a human face but also from the human body appearance. The super-resolution for a human body image is difficult because the appearances of person images vary according to the color of clothing and the posture of persons. Thus, we focus on the high-frequency components that could restore the lost high-frequency components of the low-resolution image regardless to the variation of the clothing. Therefore, the purpose of the work presented in this paper is to apply the exemplar-based super-resolution using high-frequency components for a low-resolution human body image to generate a high-resolution human body image so that both computer systems and humans can identify persons more accurately. As a result of experiments, we confirmed the effectiveness of the proposed super-resolution method.

DOI： 10.5220/0004686101150121

Sakaiにおけるi18nとl10n ～現状と課題～

出口大輔

大学ICT推進協議会（AXIES） 2014.12.11

名古屋大学における情報サービスの運用改善を目的としたシステムトラブル対応DBの構築

瀬川午直, 出口大輔, 渥美紀寿, 加藤芳秀, 嶋田創, 荻野正雄, 小川泰弘, 大野誠寛, 川田良文, 山田一成

大学ICT推進協議会（AXIES） 2014.12.12

車両部位検出を利用した回帰による車両台数推定

新村文郷, 出口大輔, 井手一郎, 村瀬洋

画像センシングシンポジウム(SSII) 2014.6.13

Event date： 2014

Language：Japanese Presentation type：Poster presentation

Venue：パシフィコ横浜アネックスホール

安全運転支援において，周囲の道路状況を理解することは重要である．自車周囲を走行する他車両の台数の把握は，道路状況の理解に役立つ重要な情報と考えられる．本発表では，車載カメラ画像中から車両の台数を推定するため，車両部位検出を利用した回帰による車両台数推定手法を提案する．車両を検出して台数を数える手法では，車両のオクルージョンにより検出精度が低下する問題がある．この問題を回避するため，提案手法では車両部位を検出して台数を数えるアプローチを用いる．車両の部位数から台数を推定する場合，車両の台数と部位数の関係は複雑であり，部位数から車両台数を一意に求めることは難しい．そこで，回帰を導入することにより，推定誤差の低減を図る．提案手法の有効性を確認するため，実環境で撮影した車載カメラ画像に対して提案手法を適用して車両台数を推定し，推定精度を評価した．評価の結果，提案手法は平均絶対誤差1.11 台の精度で車両台数を推定可能なことを確認した．

A Study on Tastes Estimation of Food Based on Food Images and Ingredients

Hiroki Matsunaga, Keisuke Doman, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (DE) 2014.9.11

A Preliminary Study on Hand Waving Detection Using an Infrared Sensor Array

Chisato Toriyama, Takashi Hosono, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2014 2014.9.8

A study on an effective camera arrangement toward gaze awareness by eye images synthesis for teleconferencing

Takuya Inoue, Tomokazu Takahashi, Takatsugu Hirayama, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2014 2014.9.8

A study on effective features for pedestrian detection using a low resolution LIDAR

Yoshinori Ichikawa, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hideaki Misawa, Utsushi Sakai

Tokai-Section Joint Conference on Electrical, Electronics, Information, and Related Engineering 2014 2014.9.8

Vision-based Vehicle Localization using a Visual Street Map with Embedded SURF Scale International conference

David Robert Wong, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Computer Vision in Vehicle Technology with Special Session on Micro Aerial Vehicles (CVVT2014) 2014.9.6

Event date： 2014

Language：English Presentation type：Oral presentation (general)

Venue：Zurich, Switzerland

Accurate vehicle positioning is important not only for in-car navigation systems but is also a requirement for emerging autonomous driving methods. Consumer level GPS are inaccurate in a number of driving environments such as in tunnels or areas where tall buildings cause satellite shadowing. Current vision-based methods typically rely on the integration of multiple sensors or fundamental matrix calculation which can be unstable when the baseline is small.

In this paper we present a novel visual localization method which uses a visual street map and extracted SURF image features. By monitoring the difference in scale of features matched between input images and the visual street map within a Dynamic Time Warping framework, stable localization in the direction of motion is achieved without calculation of the fundamental or essential matrices.

We present the system performance in real traffic environments. By comparing localization results with a high accuracy GPS ground truth, we demonstrate that accurate vehicle positioning is achieved.

TransifexによるSakai 翻訳環境の設定

出口大輔

Ja Sakai アンカンファレンス 2014.9.4

A preliminary study on the estimation of human orientation using an integrated RGB-D sensor

Fumito Shinmura, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

IEICE Technical Report (PRMU) 2014.9.2

Spatial People Density Estimation from Multiple Viewpoints by Memory Based Regression International conference

Yoshimune Tabuchi, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takayuki Kurozumi, Kunio Kashino

22nd IAPR International Conference on Pattern Recognition (ICPR2014) 2014.8.27

Event date： 2014

Language：English Presentation type：Poster presentation

Venue：Stockholm, Sweden

Crowd analysis using cameras has attracted much attention for public safety and marketing. Among techniques of the crowd analysis, we focus on spatial people density estimation which estimates the number of people for each small area in a floor region. However, spatial people density cannot be estimated accurately for an area far from the camera because of the occlusion by people in a closer area. Therefore, we propose a method using a memory based regression method with images captured from cameras from multiple viewpoints. This method is realized by looking up a table that consists of correspondences between people density maps and crowd appearances. Since the crowd appearances include situations where various occlusions occur, an estimation robust to occlusion should be realized. In an experiment, we examined the effectiveness of the proposed method.

A Study on Prediction of Driver’s Overlooking Probability by Image Processing Adaptive to Visual Fields of View

Ryunosuke Tanishige, Keisuke Doman, Daisuke Deguchi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

17th Meeting on Image Recognition & Understanding (MIRU2014) 2014.7.31

Baggage detection from multi-viewpoints human images

Yasuhiro Asai, Kento Nishibori, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

17th Meeting on Image Recognition & Understanding (MIRU2014) 2014.7.30

拡張Census Transformを用いた道路面経時差分による車載カメラ映像からの障害物検出

久徳遙矢, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2014.7.29

車両部位の検出数と検出信頼度を利用した回帰による車両台数推定

新村文郷, 出口大輔, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2014.7.29

Human tracking via thermo-spatial sensitive histogram

Takashi Hosono, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomoyoshi Aizawa, Masato Kawade

17th Meeting on Image Recognition & Understanding (MIRU2014) 2014.7.29

Removal of Moving Objects From Frontal In-vehicle Camera Videos Based on Adaptive Selection of Reference Image

Toru Kotsuka, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

17th Meeting on Image Recognition & Understanding (MIRU2014) 2014.7.29

Selection of news story series based on the responses by SNS users for the summarization of multiple news videos

Kosuke Kato, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2014.10.9

Scene duplicate detection from news videos using image-audio matching focusing on human faces International conference

Haruka Kumagai, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

16th IEEE International Symposium on Multimedia (ISM2014) 2014.12.10

A Proposal of Encoding Marker which is Robust against Blur and easy to Detect

Norimasa Kobori, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (IE) 2014.12.4

Event detection based on twitter enthusiasm degree for generating a sports highlight video International conference

Keisuke Doman, Taishi Tomita, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

ACM International Multimedia Conference (ACM-MM) 2014.11.5

Event date： 2014

Language：English Presentation type：Poster presentation

Venue：Orlando, Florida, USA

This paper presents a Twitter-based event detection method based on Twitter Enthusiasm Degrees (TED)" toward generating a highlight video of a sports game. Existing methods not only depend on both languages and sports types but also often falsely detect non-target events. In contrast, the proposed method detects sports events using TEDs calculated from several kinds of string features independent of languages and sports. We applied the proposed method to actual sports games, and compared the detected events with the events present in broadcasted highlight videos, and confirmed the effectiveness and the language and sports type independencies of the proposed method."

Human Tracking using a Far-Infrared Sensor Array and a Thermo-Spatial Sensitive Histogram International conference

細野峻司, 高橋友和, 出口大輔, 井手一郎, 村瀬洋, 相澤知禎, 川出雅人

2nd Workshop on User-Centred Computer Vision 2014.11.1

A Collaborative Report on The Open Apereo 2014 Conference

Yuji Tokiwa, Soichiro Fujii, Makoto Miyazaki, Daisuke Deguchi, Naoshi Hiraoka, Shoji Kajita

IPSJ SIG Technical Report (CLE) 2014.10.24

A study on image transformation of eye areas for synthesizing eye-contacts in video conferencing

Takuya Inoue, Tomokazu Takahashi, Takatsugu Hirayama, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takayuki Kurozumi, Kunio Kashino

IEICE Technical Report (PRMU) 2014.10.10

Prediction of Driver's Pedestrian Detectability by Image Processing Adaptive to Visual Fields of View International conference

Ryunosuke Tanishige, Daisuke Deguchi, Keisuke Doman, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

2014 IEEE Conference on Intelligent Transportation Systems (ITSC2014) 2014.10.10

A study on features for pedestrian detection using a low resolution LIDAR

Yoshinori Ichikawa, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hideaki Misawa, Utsushi Sakai

IEICE Technical Report (PRMU) 2014.10.9

A study on the reference image selection for the removal of moving objects from frontal in-vehicle camera videos

Toru Kotsuka, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2014.10.9

A Collaborative Report on The Open Apereo 2013 Conference

Yuji Tokiwa, Makoto Miyazaki, Daisuke Deguchi, Naoshi Hiraoka, Shoji Kajita

IPSJ SIG Technical Report (CLE) 2013.12.15

複数フレーム型と学習型の組み合わせによる低解像度顔画像の超解像

吉田智成, 高橋友和, 出口大輔, 井手一郎, 村瀬洋

動的画像処理実利用化ワークショップ(DIA) 2013.3.7

Event date： 2013

Language：Japanese Presentation type：Oral presentation (general)

Venue：静岡大学浜松キャンパス

監視カメラ映像中の顔画像認識において，顔領域が低解像度であることは認識精度の低下を招く．この問題に対して我々は，顔向きの変化を利用した複数フレーム型超解像手法を提案してきた．しかし，複数フレーム型超解像には，画像が低解像度になるにつれ，必要な高周波成分を復元することが困難になるという問題がある．そこで本発表では，複数フレーム型超解像と学習型超解像を組み込み合わせた手法を提案する．学習型超解像は，大量の顔画像から高解像度化に必要な顔の知識を学習し，それを用いて低解像度画像から高解像度画像を生成する技術である．これにより，複数フレーム型超解像では復元しきれなかった高周波成分の復元を図る．実際に撮影した動画像を用いた実験の結果から提案手法の有効性を確認した．

An evaluation of a visibility estimation method for traffic signals under rainy weather condition using a large dataset.

Ryuhei Sato, Keisuke Doman, Daisuke Deguchi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Naoki Nitanda

Dynamic Image Processing for Real Application workshop (DIA2013) 2013.3.7

Pedestrian detection with iterative generative learning

Hidefumi Yoshida, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takashi Machida, Yoshiko Kojima

Dynamic Image Processing for Real Application workshop (DIA2013) 2013.3.7

Detection of Biased Broadcast Sports Video Highlights by Attribute-Based Tweets Analysis International conference

Takashi Kobayashi, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Lecture Note in Computer Science 2013.1.9

Event date： 2013

Language：English Presentation type：Poster presentation

Venue：黄山柏瑞酒店（中華人民共和国安徽省黄山市）

We propose a method for detecting biased-highlights in a broadcast sports video according to viewers’ attributes obtained from a large number of tweets. Recently, Twitter is widely used to make real-time play-by-play comments on TV programs, especially on sports games. This trend enables us to effectively acquire the viewers’ interests in a large mass. In order to make use of such tweets for highlight detection in broadcast sports video, the proposed method first performs an attribute analysis on the set of tweets issued by each user to classify which team he/she supports. It then detects biased-highlights by referring to the number of tweets made by viewers with a specific attribute.

DOI： 10.1007/978-3-642-35728-2_35

A Study of Gaze Estimation Using Head and Body Pose Information International conference

Nobuhiro Funatsu, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

International Workshop on Advanced Image Technology (IWAIT) 2013 2013.1.8

Event date： 2013

Language：English Presentation type：Oral presentation (general)

Venue：Nagoya University

Gaze estimation from an image is an important technique for tasks such as driver monitoring and measuring of advertising effectiveness. For this, most existing methods require a high quality image of eyes. However, It is difficult to obtain the eye images when eye occlusion occurs due to sunglasses or face rotation. Another approach approximates head directions to gaze directions. However, the gaze direction is affected not only by the head direction but also by the body direction. Thus, we are studying a method that estimates the gaze direction accurately using information on both head and body pose directions. Experimental result showed that the proposed method could estimate gaze directions more accurately than by using the information on only head directions.

Automatic Construction of Traffic Sign Detector Based on Simultaneous Gathering of Training Samples

Daisuke Deguchi, Hiroshi Murase

International Workshop on Advanced Image Technology (IWAIT) 2013 2013.1.7

Event date： 2013

Language：English Presentation type：Oral presentation (general)

Venue：Nagoya University, Japan

This paper proposes a method for automatic construction of traffic sign detector based on simultaneous gathering of training samples from in-vehicle camera image sequences. Most existing methods for object detection based on AdaBoost classifier require various training samples for constructing an accurate detector. In the case of traffic sign detection, traffic sign images having various appearances should be prepared as positives before constructing the detector to achieve accurate traffic sign detection from in-vehicle camera images. In addition to the traffic sign images, various background images should also be prepared as negatives to reduce false alarms. However, since they are prepared manually by specifying their clipping rectangles in in-vehicle camera images, their preparation cost is quite expensive. To solve this problem, our group has proposed a method for obtaining positive and negative training samples automatically from in-vehicle camera image sequences. By extending our previous work, this paper presents a method of automatic construction of traffic sign detector that uses the state-of-the-art image features and Ada-Boost classifier. We conducted experiments with in-vehicle camera images containing traffic signs with various backgrounds. Experimental results showed the effectiveness of the proposed method.

A study on detection of belongings from a human image using their category and direction

Yasuhiro Asai, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2013.12.13

Summarizing a Domestic Cooking Video According to the Description of a Cooking Recipe

Yasuhiro Hayashi, Keisuke Doman, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2013.3.11

A Study on Exemplar Based Super Resolution for Low Resolution Images of Human Body

Kento Nishibori, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2013.9.3

TransifexによるSakai CLE 翻訳

出口大輔

Ja Sakai アンカンファレンス 2013.8.21

Exemplar-Based Super-Resolution for Low-Resolution Images of Human Body

Kento Nishibori, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

16th Meeting on Image Recognition & Understanding (MIRU2013) 2013.7.31

エピポーラ幾何に基づく画像間距離を用いた車載カメラ映像データベース探索による自車位置推定

久徳遙矢, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2013.7.30

A study on possessing detection of belongings from human image using human direction

Yasuhiro Asai, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

16th Meeting on Image Recognition & Understanding (MIRU2013) 2013.7.1

Localization of point heat sources using the spatial characteristic of a sensor in an infrared sensor array

Takashi Hosono, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

16th Meeting on Image Recognition & Understanding (MIRU2013) 2013.7.1

Automatic Pedestrian Segmentation Using Grab-cut and Active Shape Model Feedback

Esmaeil Pourjam, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

16th Meeting on Image Recognition & Understanding (MIRU2013) 2013.7

Pedestrian Detection by Scene Dependent Classifiers with Generative Learning International conference

Hidefumi Yoshida, Daichi Suzuo, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takashi Machida, Yoshiko Kojima

2013 IEEE Intelligent Vehicles Symposium (IV2013) 2013.6.25

Event date： 2013

Language：English Presentation type：Poster presentation

Venue：Gold Coast, Australia

Recently, pedestrian detection from in-vehicle camera images is becoming an crucial technology for Intelligent Transportation Systems (ITS). However, it is difficult to detect pedestrians accurately in various scenes by obtaining training samples. To tackle this problem, we propose a method to construct scene dependent classifiers to improve the accuracy of pedestrian detection. The proposed method selects an appropriate classifier based on the scene information that is a category of appearance associated with location information. To construct scene dependent classifiers, the proposed method introduces generative learning for synthesizing scene dependent training samples. Experimental results showed that the detection accuracy of the proposed method outperformed the comparative method, and we confirmed that scene dependent classifiers improved the accuracy of pedestrian detection.

Surrounding environment recognition using in-vehicle camera

Daisuke Deguchi, Keisuke Doman, Ichiro Ide, Hiroshi Murase

2013.6.10

Segmentation of Human Instances Using Grab-cut and Active Shape Model Feedback International conference

Esmaeil Pourjam, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IAPR Conference on Machine Vision Applications (MVA) 2013 2013.5.21

A Study on People Counting from Multiple Cameras Using Visual Hull

Yoshimune Tabuchi, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomonori Izumitani, Kunio Kashino

2013 IEICE General Conference 2013.3.22

A preliminary study on personal adaptation for predicting pedestrian's detectability

Ryunosuke Tanishige, Keisuke Doman, Daisuke Deguchi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Naoki Nitanda

2013 IEICE General Conference 2013.3.21

A Study on Belongings Recognition from Human Image in Surveillance Video

Yasuhiro Asai, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

2013 IEICE General Conference 2013.3.20

A study on localization of point heat sources using an infrared sensor array

Takashi Hosono, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Yoshihisa Ijiri

2013 IEICE General Conference 2013.3.20

A Study on Gaze Estimation from Person Images Using Head Pose Information

Nobuhiro Funatsu, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2013.3.14

A study on a pedestrian detector adaptive to driving environment using in-vehicle camera and GPS

Daichi Suzuo, Hidefumi Yoshida, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takashi Machida, Yoshiko Kojima

IEICE Technical Report (PRMU) 2013.3.14

Annual report on activities of Sakai deployment in Nagoya University

Daisuke Deguchi, Akifumi Goto, Shigeki Ohira, Yoshihiro Ohta, Nao Tanoue, Takahiro Nakatsukasa, Kensaku Mori

Ja Sakai Annual Conference 2013 2013.3.14

Estimation of the Representative Story Transition in a Choronological Semantic Structure of News Topics

Kosuke Kato, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2013.3.12

Event Detection based on Twitter Enthusiasm Degree for Making a Sports Highlight Video

Taishi Tomita, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2013.3.12

Extraction of Tips on Taste in Supplementary Information of Cooking Recipes

Satoshi Yokoi, Yasuhiro Hayashi, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase, Yuto Mizuno, Tomoko Kojiri, Kazuhisa Seta

IEICE Technical Report (MVE) 2013.3.11

Ingredients Estimation in a Dish by Learning from a Large Number of Recipes with Images

Hiroki Matsunaga, Satoshi Yokoi, Yasuhiro Hayashi, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2013.3.11

Generation of a scenery video with no obstacle from a video captured from inside a vehicle

Toru Kotsuka, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical and Related Engineering 2013 2013.9.25

A study on a driving environment adaptive pedestrian detection leveraging location information

Daichi Suzuo, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hiroyuki Ishida, Yoshiko Kojima

Tokai-Section Joint Conference on Electrical and Related Engineering 2013 2013.9.25

Scene Duplicate Detection from News Videos Using Visual Features and Audio Features

Haruka Kumagai, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Technical Report (MVE) 2013.9.26

A preliminary study on the prediction of pedestrian's detectability considering drivers' characteristics

Ryunosuke Tanishige, Daisuke Deguchi, Keisuke Doman, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Utsushi Sakai

IEICE Technical Report (PRMU) 2013.12.12

Localization of point heat sources using a low resolution infrared sensor array

Takashi Hosono, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2013.12.12

Exemplar-Based Super-Resolution of Human Body Image in Surveillance Video

Kento Nishibori, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Vision Engineering Workshop (ViEW) 2013 2013.12.5

監視カメラシステムのための低解像度人体画像の超解像に関する検討

西堀研人, 高橋友和, 出口大輔, 井手一郎, 村瀬洋

計測自動制御学会システム・情報部門学術講演会（SSI） 2013.11.18

Event date： 2013

Language：Japanese Presentation type：Poster presentation

Venue：滋賀県・大津・ピアザ淡海

防犯を目的とした監視カメラの設置が増えてきており，不審者の検出や人物照合等に用いられている．このような広域を監視するカメラを用いた場合，人物は低解像度で撮影されることが多く人物の照合が困難となる．低解像度画像を高解像度化する技術として，超解像技術が用いられている．しかし，人体の画像は姿勢や服装のように外見の変化が大きく超解像が困難である．そこで，本研究では低解像度の人体画像を高解像度化することで，人が見ても機械が処理をしても人物照合をより正確に行うことができる高解像度の人体画像を生成することを目的とする．ここでは，大量の人物画像からなる学習用画像を用いて1枚の低解像度画像から高解像度画像を生成する学習型超解像方式を適用し，人体画像の超解像について検討を行う．

Scene dependent classifiers for pedestrian detection International conference

Hidefumi Yoshida, Daichi Suzuo, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

International Joint Workshop on Advanced Sensing / Visual Attention and Interaction (ASVAI2013) 2013.11.5

Automatic authoring of a domestic cooking video based on the description of cooking instructions International conference

Yasuhiro Hayashi, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

5th International Workshop on Multimedia for Cooking and Eating Activities (CEA'13) 2013.10.21

Blur-invariant Traffic Sign Recognition Using Compact Local Phase Quantization International conference

Saleh Aly, Daisuke Deguchi, Hiroshi Murase

2013 IEEE Conference on Intelligent Transportation Systems (ITSC2013) 2013.10.8

Construction of a traffic sign detector based on voting type co-training International conference

Yuji Kojima, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2013 IEEE Conference on Intelligent Transportation Systems (ITSC2013) 2013.10.8

A study on people density estimation using multiple cameras

Yoshimune Tabuchi, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takayuki Kurozumi, Kunio Kashino

IEICE Technical Report (PRMU) 2013.10.3

Prediction of Pedestrian Detectability for Drivers by Image Processing and its Driver Adaptation International conference

Ryunosuke Tanishige, Daisuke Deguchi, Keisuke Doman, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Naoki Nitanda

6th Biennial Workshop on Digital Signal Processing for In-Vehicle Systems (DSP2013) 2013.9.30

Event date： 2013

Language：English Presentation type：Oral presentation (general)

Venue：Korea University, Seoul, Korea

In recent years, advances in pedestrian detection technology have resulted in the development of driving assistance systems that notify the drivers of the presence of pedestrians. However, warning of all of the presence of pedestrians would confuse the driver. Therefore, the driver should only be notified of the less detectable pedestrians to avoid confusion. To achieve this, it is necessary to develop a method to predict the driver’s perception performance of pedestrian detectability. This paper proposes a method that predicts the pedestrian detectability considering the difference between individual drivers. The proposed method constructs a predictor specific to each driver, in order to predict the pedestrian detectability precisely. To obtain the ground truth of the pedestrian detectability, we conducted an experiment by human subjects using images from an in-vehicle camera including pedestrians. From the comparison between the output of the proposed method and the actual detectability, we confirmed that the proposed method significantly reduces the prediction error in comparison with the existing methods.

Sakaiを中心とした教育基盤構築の現状と今後の展開

出口大輔, 後藤明史, 大平茂輝, 太田芳博, 田上奈緒, 中務孝広, 森健策

大学ICT推進協議会（AXIES） 2012.12.17

A Collaborative Report on The 13th Sakai Conference

Yuji Tokiwa, Makoto Miyazaki, Ryuichi Matsuba, Daisuke Deguchi, Shoji Kajita

IPSJ SIG Technical Report (CLE) 2012.11.3

Subtraction-Based Forward Obstacle Detection Using Illumination Insensitive Feature for Driving-Support International conference

Haruya Kyutoku, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

Computer Vision in Vehicle Technology: From Earth to Mars (CVVT2012) 2012.10.13

Event date： 2012

Language：English Presentation type：Oral presentation (general)

Venue：Firenze, Italy

This paper proposes a method for detecting general obstacles on a road by subtracting present and past in-vehicle camera images.
The image-subtraction-based object detection approach can be applied to detect any kind of obstacles although the existing learning-based methods detect only specific obstacles.
To detect general obstacles, the proposed method first computes a frame-by-frame correspondence between the present and the past in-vehicle camera image sequences, and then registrates road surfaces between the frames.
Finally, obstacles are detected by applying image subtraction to the registrated road surface regions with an illumination insensitive feature for robust detection.
Experiments were conducted by using several image sequences captured by an actual in-vehicle camera to confirm the effectiveness of the proposed method.
The experimental results shows that the proposed method can detect general obstacles accurately at a distance enough to avoid them safely even in situations with different illuminations.

DOI： 10.1007/978-3-642-33868-7_51

Visibility Estimation of Traffic Signals under Rainy Weather Conditions for Smart Driving Support International conference

Ryuhei Sato, Keisuke Doman, Daisuke Deguchi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

2012 IEEE Conference on Intelligent Transportation Systems (ITSC2012) 2012.9.19

Event date： 2012

Language：English Presentation type：Oral presentation (general)

Venue：Anchorage, Alaska, USA,

The aim of this work is to support a driver by
notifying the information of traffic signals in accordance with
their visibility. To avoid traffic accidents, the driver should
detect and recognize surrounding objects, especially traffic
signals. However, when driving a vehicle under rainy weather
conditions, it is difficult for drivers to detect or to recognize
objects existing in the road environment in comparison with fine
weather conditions. Therefore, this paper proposes a method
for estimating the visibility of traffic signals for drivers under
rainy weather conditions by image processing. The proposed
method is based on the concept of visual noise known in the
field of cognitive science, and extracts two types of visual noise
features which ware considered that they affect the visibility of
traffic signals. We expect to improve the accuracy of visibility
estimation by combining the visual noise features with the
texture feature introduced in a previous work. Experimental
results showed that the proposed method could estimate the
visibility of traffic signals more accurately under rainy weather
conditions.

DOI： 10.1109/ITSC.2012.6338838

A preliminary study on a pedestrian detector adaptive to the driving environment using an in-vehicle camera

Daichi Suzuo, Hidefumi Yoshida, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takashi Machida, Yoshiko Kojima

IEICE Technical Report (PRMU) 2012.9.3

Virtual View Generation using Clustering based Local View Transition Model International conference

Xi Li, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

ACCV Workshop on Face Analysis: The Intersection of Computer Vision and Human Perception 2012.11.6

Event date： 2012

Language：English Presentation type：Oral presentation (general)

Venue：Deajeon Convention Center, Daejeon, Korea

This paper presents an approach for realistic virtual view generation using appearance clustering based local view transition model, with its target application on cross-pose face recognition. Previously, the traditional global pattern based view transition model (VTM) method was extended to its local version called LVTM, which learns the linear transformation of pixel values between frontal and non-frontal image pairs using partial image in a small region for each location, rather than transforming the entire image pattern. In this paper, we show that the accuracy of the appearance transition model and the recognition rate can be further improved by better exploiting the inherent linear relationship between frontal-nonfrontal face image patch pairs. For each specific location, instead of learning a common transformation as in the LVTM, the corresponding local patches are first clustered based on appearance similarity distance metric and then the transition models are learned separately for each cluster. In the testing stage, each local patch for the input non-frontal probe image is transformed using the learned local view transition model corresponding to the most visually similar cluster. The experimental results on a real-world face dataset demonstrated the superiority of the proposed method in terms of recognition rate.

Detection and classification of repetitious human motions combining shift variant and invariant features International conference

Ichiro Ide, Taku Kuhara, Daisuke Deguchi, Tomokazu Takahashi, Hiroshi Murase

3rd International Conference on Emerging Security Technologies (EST2012) 2012.9

多数決型co-trainingによる道路標識検出器の構築に関する検討

児島勇司, 出口大輔, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2012.8.8

顔と体の姿勢情報を利用した人物動画像からの視線方向推定に関する検討

船津暢宏, 高橋友和, 出口大輔, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2012.8.8

Event date： 2012

Language：Japanese Presentation type：Poster presentation

Venue：福岡国際会議場

カメラを用いて人物の視線方向を推定する技術が注目されている．これに関して，低解像度や遮蔽などが原因で画像中から人物の目領域を検出するのが困難な場合に，顔の向きを視線方向の代わりとして利用する研究がある．しかしながら，実際には顔の向きの他にも，体の向きやそれらの時間変化，人物がおかれている状況なども視線方向に影響を与える要因として考えられる．そこで本研究では，これらの情報を利用して視線方向をより高精度に推定することを目的としている．発表ではそれらの要因のうち，特に顔の向きと体の向き着目し，体に対する顔の向きと視線方向との関係を被験者実験により調査した結果について報告する．さらに，その調査結果に基づいた視線方向推定を行い，その推定誤差を評価した．その結果，体に対する顔の向きを利用した場合，顔の向きを視線方向として利用する場合よりも推定誤差が平均 14.9 度小さくなることを確認した．

Estimation of traffic sign visibility considering global features in an entire scene

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

15th Meeting on Image Recognition & Understanding (MIRU2012) 2012.8.8

過去の車載カメラ映像との時空間差分による不特定障害物検出

久徳遙矢, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2012.8.7

Event date： 2012

Language：Japanese Presentation type：Poster presentation

Venue：福岡国際会議場

本研究の目的は，前方を向いた車載カメラ映像から障害物を検出することである．車載カメラ映像からの障害物検出に関する研究は広く行なわれているが，多くは車両や人物といった特定の検出対象の見えを学習して行なうものであり，事前に学習することができない，段ボール箱や積荷の落下物などの不特定の障害物への対応はできない．そこで提案手法では，同一地点における過去の車載カメラ映像との差分を用いて不特定の前方障害物を検出する．しかし，過去の走行映像は走行位置の違いによる視点のずれを含み，直接的に差分を求めることは困難である．そこで，まず既存手法により現在と過去の映像中のフレーム間対応付けを行なう．そして，対応付いたフレーム同士の道路面を射影変換によって位置合わせする．最後に，対象までの距離を考慮した道路面時空間画像差分により障害物を検出する．評価実験から，ボールなどの不特定の障害物を検出できることを確認した．

Visibility Estimation of Traffic Signals in Rainy Conditions Considering the Visual Noise

Ryuhei Sato, Keisuke Doman, Daisuke Deguchi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

15th Meeting on Image Recognition & Understanding (MIRU2012) 2012.8.7

Robust Face Super-Resolution Using Free-Form Deformations For Low-Quality Surveillance Video International conference

Tomonari Yoshida, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2012 IEEE International Conference on Multimedia and Expo (ICME2012) 2012.7.10

Cook-Log Video Summarization by Removing Temporal Redundancy

Yasuhiro Hayashi, Keisuke Doman, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (DE) 2012.6.6

Construction of a local attraction map according to social visual attention International conference

Ichiro Ide, Jiani Wang, Masafumi Noda, Tomokazu Takahashi, Daisuke Deguchi, Hiroshi Murase

5th International Conference on Intelligent Interactive Multimedia Systems and Services (IIMSS2012) 2012.5

A study on General Obstacle Detection by Spatio-Temporal Subtraction with Past In-Vehicle Camera Image Sequence

Haruya Kyutoku, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2012.3.30

Method for displaying Images on Urban Structures by Augmented Reality

Hiroyuki Uchiyama, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takahito Kawanishi, Kunio Kashino

IEICE Technical Report (PRMU) 2012.3.29

A Preliminary Study on Image Features for Visibility Estimation of Traffic Signals in Raining Conditions

Ryuhei Sato, Keisuke Doman, Daisuke Deguchi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

2012 IEICE General Conference 2012.3.22

A Preliminary Study on the Relationship between Gaze Direction and Head Pose with Respect to Body

Nobuhiro Funatsu, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2012 IEICE General Conference 2012.3.21

A Study on Facial Image Search Using Attributes Based on Impression

Yasunori Ozaki, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

2012 IEICE General Conference 2012.3.21

Super-resolution using facial pose variation

Tomonari Yoshida, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

2012 IEICE General Conference 2012.3.21

A study on region-based matching for scene duplicate detection from news videos

Haruka Kumagai, Keisuke Doman, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2012.3.12

Digital Camera-Working for Cooking Videos Based on the Determination of Target Areas According to the Cooking Process

Wataru Hyogo, Yasuhiro Hayashi, Masafumi Noda, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2012.3.12

Extraction of Speech Shots Focusing on Visual and Audio Features within and between Shots

Shogo Kumagai, Keisuke Doman, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2012.3.12

Video retrieval by generic object recognition using spatio-temporal CoHOG features

Shogo Nakamura, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

Dynamic Image Processing for Real Application workshop (DIA2012) 2012.3.9

A Study on Image Features Considering Properties of Visual Search for Estimation of Pedestrian Detectability

Masashi Wakayama, Keisuke Doman, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

Dynamic Image Processing for Real Application workshop (DIA2012) 2012.3.8

Prediction of driving behavior using gaze information and vehicle information

Tatsuki Kamisaka, Masafumi Noda, Yoshito Mekada, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Dynamic Image Processing for Real Application workshop (DIA2012) 2012.3.8

Integration of generative learning and multiple pose classifiers for pedestrian detection International conference

Hidefumi Yoshida, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Kunihiro Goto, Yoshikatsu Kimura, Takashi Naito

International Conference on Computer Vision Theory and Applications (VISAPP) 2012 2012.2.26

Event date： 2012

Language：English Presentation type：Oral presentation (general)

Venue：Rome, Italy

Recently, pedestrian detection from in-vehicle camera images is becoming an important technology in ITS (Intelligent Transportation System).
However, it is difficult to detect pedestrians stably due to the variety of their poses and their backgrounds.
To tackle this problem, we propose a method to detect various pedestrians from in-vehicle camera images by using multiple classifiers corresponding to various pedestrian pose classes.
Since pedestrians’ pose varies widely, it is difficult to construct a single classifier that can detect pedestrians with various poses stably.
Therefore, this paper constructs multiple classifiers optimized for variously posed pedestrians by classifying pedestrian images into multiple pose classes.
Also, to reduce the bias and the cost for preparing numerous pedestrian images for each pose class for learning, the proposed method employs a generative learning method.
Finally, the proposed method constructs multiple classifiers by using the synthesized pedestrian images.
Experimental results showed that the detection accuracy of the proposed method outperformed comparative methods, and we confirmed that the proposed method could detect variously posed pedestrians stably.

DOI： 10.5220/0003817305670572

Face recognition based on virtual frontal view generation using LVTM with local patches clustering

Xi Li, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2012.2.9

Event date： 2012

Language：English Presentation type：Oral presentation (general)

Venue：東北大学

One of the major difficulties encountered by face recognition is the varying poses caused by in-depth rotations.
The intra-person appearance differences caused by rotations are often larger than the inter-person differences, which makes
the traditional face recognition methods such as eigen-face infeasible. This paper presents a framework for face recognition
across pose based on virtual frontal view generation using Local View Transition Model(LVTM) with local patches clustering.
Previous study on LVTM shows that more accurate appearance transition model can be achieved by first dividing the original
face image plane into overlapping local patch regions and then the learned transition models for each patch are aggregated for
the final transformation. In this paper we show that the accuracy the appearance transition model and the recognition rate can
be further improved by better exploiting the inherent linear relationship between frontal-nonfrontal face image pairs. This is
achieved based on the observation that variations in appearance caused by pose are closely related to the corresponding 3D
face structure and intuitively frontal-nonfrontal pairs from more similar local 3D face structures should have a stronger linear
relationship. For each specific location, instead of learning a common transformation as in LVTM, the corresponding local
patches are first clustered based on appearance similarity distance metric and then the transition models are learned separately
for each cluster. In the testing stage, each local patch for the input nonfrontal probe image is transformed using the learned
local view transition model corresponding to the most visually similar cluster. The experimental results on real life face dataset
demonstrate the effectiveness of the proposed method.

A study on a method for high-accuracy detection of a pedestrian holding an umbrella with generative learning

Hidefumi Yoshida, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takashi Machida, Yoshiko Kojima

IEICE Technical Report (PRMU) 2012.9.3

A Study on Event Detection in a Sports Game using Twitter

Taishi Tomita, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

HCG Symposium 2012 2012.12.11

Estimation of the human performance for pedestrian detectability based on visual search and motion features International conference

Masashi Wakayama, Daisuke Deguchi, Keisuke Doman, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

21st IAPR International Conference on Pattern Recognition (ICPR2012) 2012.11.14

Event date： 2012

Language：English Presentation type：Poster presentation

Venue：Tsukuba, Japan

This paper proposes a method for estimating the human performance of pedestrian detectability from in-vehicle camera images in order to warn a driver of the positions of pedestrians in an appropriate timing. By introducing features related to visual search and motion of the target, the proposed method estimates the detectability of pedestrians accurately. Support Vector Regression (SVR) is used to estimate the detectability. Here, SVR is trained using features calculated by the proposed method with the ground truth obtained through experiments with human subjects. From experiments using in-vehicle camera images, we confirmed that the proposed features were effective to estimate the detectability of pedestrians.

Looking back on past PRMU Algorithm Contests

Daisuke Deguchi, Yoshinari Kameda, Itaru Kitahara, Kazuaki Kondo, Atsushi Shimada, Shinsaku Hiura

IEICE Technical Report (PRMU) 2012.9.3

A Study on Spatio-Temporal CoHOG Features for Recognition of Generic Objects in Video

Shogo Nakamura, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2011.12.15

PRMU Algorithm Contest 2010 "Lock on targets! - object tracking -"

Daisuke Deguchi, Hiroshi Murase, Kazuaki Umeda, Masataka Saito, Kenichiro Fuji, Shingo Yamashita, Yuki Suetsugu, Syota Takai, Ryuta Sato, Takuma Maruyama

IEICE Technical Report (PRMU) 2011.3

Pedestrian Detection from In-vehicle Camera Images using Scene Context Information

Daisuke Hamada, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

2011 IEICE General Conference 2011.3

Pedestrian Detection with Generative Learning Method Considering Varying Pose

Hidefumi Yoshida, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Kunihiro Goto, Yoshikatsu Kimura, Takashi Naito

2011 IEICE General Conference 2011.3

Person Re-identification at a Room Entrance by Adaptive Feature Selection

Takuya Honda, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2011.3

Proposal of a Sight-seeing Map with Visual Classification and Presentation of Photos on the Web

Jiani Wang, Masafumi Noda, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2011.3

Scene Segmentation of a Wedding Party Video by Scenario-based Matching with Example Videos

Kazuki Sawai, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2011.3

Study on super-resolution under facial pose variation for low-resolution face recognition

Tomonari Yoshida, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

2011 IEICE General Conference 2011.3

Summarizing sports video by on-the-spot comments on Twitter

Takashi Kobayashi, Masafumi Noda, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2011.3

Summarizing sports video by on-the-spot comments on Twitter

Takashi Kobayashi, Masafumi Noda, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

2011.3

Video-based Generic Object Recognition by Combining Motion Features and BoF

Shogo Nakamura, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2011.1.21

Quantification of the Visibility of Pedestrians Based on Integration of Local and Global Features

Masashi Wakayama, Keisuke Doman, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

IEICE Technical Report (PRMU) 2011.1

A study on a method for stable pedestrian detection against pose changes with generative learning

Hidefumi Yoshida, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Kunihiro Goto, Yoshikatsu Kimura, Takashi Naito

IEICE Technical Report (PRMU) 2011.5.20

Advertisements on Urban Structures by Augmented Reality

Hiroyuki Uchiyama, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takahito Kawanishi, Kunio Kashino

Vision Engineering Workshop (ViEW) 2011 2011.12.9

Multi-frame super-resolution for low resolution QR-code recognition

Yuji Kato, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

Vision Engineering Workshop (ViEW) 2011 2011.12.9

Road-image Map Construction Using Low-resolution Aerial Image and In-vehicle Camera Images

Masafumi Noda, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Yoshiko Kojima, Takashi Naito

Vision Engineering Workshop (ViEW) 2011 2011.12.9

Detection of Inconsistency between Subject and Speaker based on the Co-occurrence of Lip Motion and Voice Towards Speech Scene Extraction from News Videos International conference

Shogo Kumagai, Keisuke Doman, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2011 IEEE International Symposium on Multimedia (ISM2011) 2011.12.6

Event date： 2011

Language：English Presentation type：Oral presentation (general)

Venue：Dana Point, California USA

We propose a method to detect the inconsistency between a subject and the speaker for extracting speech scenes from news videos.
Speech scenes in news videos contain a wealth of multimedia information, and are valuable as archived material.
In order to extract speech scenes from news videos, there is an approach that uses the position and size of a face region.
However, it is difficult to extract them with only such approach, since news videos contain non-speech scenes where the speaker is not the subject, such as narrated scenes.
To solve this problem, we propose a method to discriminate between speech scenes and narrated scenes based on the co-occurrence between a subject's lip motion and the speaker's voice.
The proposed method uses lip shape and degree of lip opening as visual features representing a subject's lip motion, and uses voice volume and phoneme as audio feature representing a speaker's voice.
Then, the proposed method discriminates between speech scenes and narrated scenes based on the correlations of these features.
We report the results of experiments on videos captured in a laboratory condition and also on actual broadcast news videos.
Their results showed the effectiveness of our method and the feasibility of our research goal.

Scene Segmentation of Wedding Party Videos by Scenario-based Matching with Example Videos International conference

Kazuki Sawai, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

19th ACM International Multimedia Conference (ACM-MM2011) 2011.12.1

A Study on Human Pose Estimation using Parametric Eigen-space Method

Nobuhiro Funatsu, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical and Related Engineering 2011 2011.9.27

A Preliminary Study on a Method for Displaying Images on Urban Structures by Augmented Reality

Hiroyuki Uchiyama, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical and Related Engineering 2011 2011.9.26

A preliminary study on the utilization of the driver's gaze information for robust segmentation of a road region

Ryuhei Sato, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical and Related Engineering 2011 2011.9.26

A study on frame localization of in-vehicle camera images using epipolar geometry

Haruya Kyutoku, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical and Related Engineering 2011 2011.9.26

An investigation of the relation between a driver's gaze and a saliency map in a driving context

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

Tokai-Section Joint Conference on Electrical and Related Engineering 2011 2011.9.26

Low resolution QR-code recognition by applying super-resolution using the property of QR-codes International conference

Yuji Kato, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

11th International Conference on Document Analysis and Recognition (ICDAR2011) 2011.9.20

Event date： 2011

Language：English Presentation type：Oral presentation (general)

Venue：Beijing, China

This paper proposes a method for low resolution QR-code recognition. A QR-code is a two-dimensional binary symbol that can embed various information such as characters and numbers. To recognize a QR-code correctly and stably,the resolution of an input image should be high. In practice,however, recognition of a QR-code is usually difficult due to
low resolution when it is captured from a distance. In this paper, we propose a method to improve the performance of low resolution QR-code recognition by using the super-resolution technique that generates a high resolution image from multiple low-resolution images. Although a QR-code is a binary pattern, it is observed as a grayscale image due to the degradation through the capturing process. Especially the pixels around the borders between white and black regions become ambiguous. To overcome this problem, the proposed method introduces a binary pattern constraint to generate super-resolved images appropriate for recognition. Experimental results showed that a recognition rate of 98% an be achieved by the proposed method, which is a 15.7% improvement in comparison with a method using a conventional super-resolution method.

A Study of Robust Multi-Frame Super Resolution for Non-Rigid Deformation of Face

Tomonari Yoshida, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2011.9.6

大局的特徴として顕著性を利用した歩行者の視認性推定

若山雅史, 道満恵介, 出口大輔, 井手一郎, 村瀬洋, 玉津幸政

画像の認識・理解シンポジウム(MIRU) 2011.7.22

車載カメラ映像中の線分の3次元位置推定と走行可能領域検出への応用

内山寛之, 高橋友和, 出口大輔, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2011.7.22

Event date： 2011

Language：Japanese Presentation type：Poster presentation

Venue：石川県金沢市金沢市文化ホール

走行可能領域検出は車両のナビゲーションや安全運転支援において重要である．市街地の構造物の多くはポールや壁面といった線分で構成されている．そこで本論文では，走行可能領域検出を目的とし，単眼カメラを用い
て市街地の線分の3次元位置推定を行う手法を提案する．カメラの姿勢が既知の場合，線分の位置を推定するためには，画像間の線分の正確な対応付けが必要となる．そのため，少数の画像間で正しい線分の対応付けを行うために，多視点幾何拘束や市街地中の線分の特徴，車両の動きの事前知識を用いる．評価実験において，推定した線分の位置から走行可能領域の検出を行い，提案手法が走行可能領域検出に十分利用可能であることを確認した．

車載カメラ画像からの高品質な道路画像の自動構築

野田雅文, 高橋友和, 出口大輔, 井手一郎, 村瀬洋, 小島祥子, 内藤貴志

画像の認識・理解シンポジウム(MIRU) 2011.7.22

Estimation of traffic sign visibility with in-vehicle camera images using temporal information

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

14th Meeting on Image Recognition & Understanding (MIRU2011) 2011.7.22

現在と過去の車載カメラ映像のフレーム間対応付け

久徳遙矢, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2011.7.21

Event date： 2011

Language：Japanese Presentation type：Poster presentation

Venue：金沢市文化ホール

本研究では，車載カメラ映像を用いた運転者支援に注目する．その際，同じ道路で撮られた過去の映像中の対応するフレームを求める事が可能になれば，様々な用途に使うことができると考えられる．そこで本稿では，高精度な現在と過去の車載カメラ映像中のフレーム間対応付け手法を提案する．同じ道路で撮られた映像同士の対応付けであっても，走行は全く同じ速度・軌跡ではないため，単純な画像照合による対応付けは困難である．そこで，まず現在と過去のフレーム間で対応点を求め，それらからフレーム間の基礎行列を求める．次に，基礎行列から求めたエピポールの位置に基づくフレーム間の距離を定義し，この尺度を用いたDP マッチングにより，フレーム同士を対応付ける．実際の車載カメラ映像を用いた評価実験の結果，提案手法の有効性を確認した．

On-road Obstacle Detection by Comparing Present and Past In-vehicle Camera Images International conference

Haruya Kyutoku, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

IAPR Conference on Machine Vision Applications (MVA) 2011 2011.6.14

Estimation of Traffic Sign Visibility Considering Temporal Environmental Changes for Smart Driver Assistance International conference

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

2011 IEEE Intelligent Vehicles Symposium (IV2011) 2011.6.7

Event date： 2011

Language：English Presentation type：Poster presentation

Venue：Baden-Baden, Germany

We propose a visibility estimation method for traffic signs considering temporal environmental changes, as a part of work for the realization of nuisance-free driver assistance systems. Recently, the number of driver assistance systems in a vehicle is increasing. Accordingly, it is becoming important to sort out appropriate information provided from them, because providing too much information may cause driver distraction. To solve such a problem, we focus on a visibility estimation method for controlling the information according to the visibility of a traffic sign. The proposed method sequentially captures a traffic sign by an in-vehicle camera, and estimates its accumulative visibility by integrating a series of instantaneous visibility. By this way, even if the environmental conditions may change temporally and complicatedly, we can still accurately estimate the visibility that the driver perceives in an actual traffic scene. We also investigate the performance of the proposed method and show its effectiveness.

Road Image Update using In-vehicle Camera Images and Aerial Image International conference

Masafumi Noda, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Yoshiko Kojima, Takashi Naito

2011 IEEE Intelligent Vehicles Symposium (IV2011) 2011.6.7

Event date： 2011

Language：English Presentation type：Poster presentation

Venue：Baden-Baden, Germany

Road image is becoming important for several
applications such as car navigation systems, traffic environment
research, city modeling. Usually, a road image can be obtained
from an aerial image but the resolution of the aerial image is
often low, or it contains occlusions by obstacles. Therefore, the
update of road image is required. In this paper, we propose a
road image mosaicing method using in-vehicle camera images
and an aerial image. We first perform image registration of road
regions between these images, and then, we generate a large road
image by performing image mosaicing of road regions in invehicle
camera images. In an experiment, we achieved resolution
improvement and occlusions removal, and also succeeded in
update of a large road image.

3-D Line Segment Reconstruction Using an In-Vehicle Camera for Free Space Detection International conference

Hiroyuki Uchiyama, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

2011 IEEE Intelligent Vehicles Symposium (IV2011) 2011.6.6

Event date： 2011

Language：English Presentation type：Poster presentation

Venue：Baden-Baden, Germany

Free space detection is very important for vehicle navigation and safe driving. 3-D line segment reconstruction
of a street is important for the free space detection because a street-view includes many line segments. For the free space
detection, we propose a method for reconstructing 3-D line segments in a streetscape using a monocular in-vehicle camera.
The 3-D reconstruction of the line segments is achieved by using each three images from an image sequence. Once accurate
camera poses of these images are obtained, one of the remaining crucial problems is to match the line segments between the
images correctly. A strategy for finding correspondence of the line segments is as follows: First, the correspondences of line
segment candidates are searched by using a two-view constraint. However, the two-view constraint has difficulty on determining
an unique correspondence geometrically. Therefore, the candidates of the line segment correspondences are reduced using
a three-view constraint. In order to improve the accuracy, the proposed method exploits a color feature of the line segment
and a preliminary knowledge of the vehicle motion. Finally, the line segments are reconstructed using the correspondences.
From an experimental result, we confirmed the effectiveness of the proposed method. Application to the free space detection
demonstrated the usefulness of the reconstructed line segments.

Intelligent Traffic Sign Detector: Adaptive Learning Based on Online Gathering of Training Samples International conference

Daisuke Deguchi, Mitsunori Shirasuna, Keisuke Doman, Ichiro Ide, Hiroshi Murase

2011 IEEE Intelligent Vehicles Symposium (IV2011) 2011.6.6

Event date： 2011

Language：English Presentation type：Poster presentation

Venue：Baden-Baden, Germany

This paper proposes an intelligent traffic sign detector using adaptive learning based on online gathering of training samples from in-vehicle camera image sequences. To detect traffic signs accurately from in-vehicle camera images, various training samples of traffic signs are needed. In addition, to reduce false alarms, various background images should also be prepared before constructing the detector. However, since their appearances vary widely, it is difficult to obtain them exhaustively by manual intervention. Therefore, the proposed method simultaneously obtains both traffic sign images and background images from in-vehicle camera images. Especially, to reduce false alarms, the proposed method gathers background images that were easily mis-detected by a previously constructed traffic sign detector, and re-trains the detector by using them as negative samples. By using retrospectively tracked traffic sign images and background images as positive and negative training samples, respectively, the proposed method constructs a highly accurate traffic sign detector automatically. Experimental results showed the effectiveness of the proposed method.

GPGPUによる高速画像処理

出口大輔

日本ロボット学会ロボット工学セミナー第62回シンポジウム「ロボットに使える画像処理技術の最前線」 2011.5.30

Event date： 2011

Language：Japanese Presentation type：Oral presentation (general)

Venue：東京大学武田先端知ビル5F 武田ホール

GPUを汎用計算に利用しようという試みであるGPGPU（General Purpose computing on GPUs）は，近年のGPUの高性能化およびその入手しやすさという特徴から，幅広い分野で高速計算に利用されるようになってきた．一方，画像処理アルゴリズムの多くは並列計算可能なものが多く，少しアルゴリズムを工夫することでCPUの数十倍の高速化を達成できるものも多く存在する．そこで，本講演ではGPGPUを手軽に利用できるCUDAを開発環境として利用し，実例を交えながら計算コストの高い画像処理を簡単に高速化できることを示す．

A Study on Road Image Generation by Mosaicing of In-Vehicle Camera Images Using Aerial Image as a Reference

Masafumi Noda, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Yoshiko Kojima, Takashi Naito

IEICE Technical Report (PRMU) 2011.5.20

Matching Motions in Remote Cooperative Cooking Videos Using a Position-invariant Motion Feature

Yasuhiro Hayashi, Hiroyuki Uchiyama, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2011.3

Prediction of driving behavior using driver's gaze information

Tatsuki Kamisaka, Masafumi Noda, Yoshito Mekada, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2011.5.20

Detection of Inconsistency between Face and Speaker Focusing on the Co-occurrence of Lip Motion and Audio

Shogo Kumagai, Keisuke Doman, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2011.5.14

A study on facial pose transformation based on learning-based local image transformation

Yuki Kono, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2011.3.1

A Report on MIRU2010 Young Researchers' Program

Toru Tamaki, Yuko Uematsu, Kazuaki Kondo, Tomoya Sakai, Atsushi Shimada, Daisuke Deguchi, Takayoshi Yamashita

IEICE Technical Report (PRMU) 2011.3

A study on a method to predict driving behavior using gaze information

Tatsuki Kamisaka, Masafumi Noda, Daisuke Deguchi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

2011 IEICE General Conference 2011.3

Construction of Traffic Sign Detector Using non-Sign Image gathered automatically based on characteristic of false positive

Mitsunori Shirasuna, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2011 IEICE General Conference 2011.3

Extraction and Recognition of Repetitive Cooking Motion Segments in Cooking Video by Periodicity Analysis of CHLAC Feature

Taku Kuhara, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2011.3

Accurate and Robust Attitude Estimation of a Moving Vehicle Using MEMS Gyroscopes and a Monocular Camera International conference

Norimasa Kobori, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

2010 Workshop on Picture Coding and Image Processing (WPCIP 2010) 2010.12.7

Event date： 2010

Language：English Presentation type：Poster presentation

Venue：Winc Aichi

In order to estimate accurate attitude of mobile robots and　vehicles, we propose a hybrid system which combines a lowcost　monocular camera with a gyro sensor. A gyro sensor has　drift errors that accumulate over time. On the other hand, a　camera cannot obtain the rotation continuously in the case　where feature points cannot be extracted from images, although　the accuracy is better than a gyro sensor. To solve　these problems, we propose a method for combining these　sensors based on an Extended Kalman Filter.

車載カメラ映像からの学習サンプルの自動収集による標識検出器の高精度化に関する検討

出口大輔, 道満恵介, 井手一郎, 村瀬洋

パターン認識・メディア理解研究会(PRMU) 2010.2

Pedestrian detection from in-vehicle camera images using knowledge of driving scenes

Daisuke Hamada, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

16th Symposium on Sensing via Image Information (SSII2010) 2010.6

自車位置推定のための空撮画像と車載カメラ画像の照合手法の検討

野田雅文, 高橋友和, 出口大輔, 井手一郎, 村瀬洋, 小島祥子, 内藤貴志

ビジョン技術の実利用ワークショップ(ViEW) 2010.12

Multimedia supplementation to a cooking recipe text for facilitating its understanding to inexperienced users International conference

Ichiro Ide, Yuka Shidochi, Yuichi Nakamura, Daisuke Deguchi, Tomokazu Takahashi, Hiroshi Murase

2nd Workshop on Cooking and Eating Activities (CEA2010) 2010.12

Frontal Face Generation from Multiple Low-Resolution Non-Frontal Faces for Face Recognition International conference

Yuki Kono, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

10th International Workshop on Visual Surveillance 2010 2010.11.1

Improvement of a traffic sign detector by retrospective gathering of training samples from in-vehicle camera image sequences International conference

Daisuke Deguchi, Keisuke Doman, Ichiro Ide, Hiroshi Murase

Computer Vision in Vehicle Technology: From Earth to Mars (CVVT2010) 2010.11

Vehicle Ego-localization by Matching In-vehicle Camera Images to an Aerial Image International conference

Masafumi Noda, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Yoshiko Kojima, Takashi Naito

Computer Vision in Vehicle Technology: From Earth to Mars (CVVT2010) 2010.11

Study on the Creation of a Scenery Category Map using Geo-tagged Photographic Images

Jiani Wang, Masafumi Noda, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2010.10

A method for estimation of traffic sign visibility based on integration of multiple image features

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

IEICE Technical Report (ITS) 2010.9

Hardware Architecture of K-Means Clustering based on Bayesian Information Criterion

Tse-Wei Chen, Chih-Hao Sun, Hsiao-Hang Su, Shao-Yi Chien, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

9th Forum on Information Technology (FIT2010) 2010.9

Marker-Free Registration for Electromagnetic Navigation Bronchoscopy under Respiratory Motion International conference

Marco Feuerstein, Takamasa Sugiura, Daisuke Deguchi, Tobias Reichl, Takayuki Kitasaka, Kensaku Mori

5th International Workshop on Medical Imaging and Augmented Reality (MIAR2010) 2010.9

QR-code recognition based on super-resolution using binary pattern constraint

Yuji Kato, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2010.9

Removal of Moving Objects from a Street-View Image by Fusing Multiple Image Sequences International conference

Hiroyuki Uchiyama, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

20th IAPR International Conference on Pattern Recognition (ICPR2010) 2010.8.1

A Study on Fast K-Means Clustering with Hierarchical Data Sampling for Image Processing

Tse-Wei Chen, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical and Related Engineering 2010 2010.8

A study on fusing images for removing moving objects from in-vehicle camera images

Hiroyuki Uchiyama, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical and Related Engineering 2010 2010.8

Classification of near-duplicate video segments based on their appearance patterns International conference

Ichiro Ide, Yuji Shamoto, Daisuke Deguchi, Tomokazu Takahashi, Hiroshi Murase

20th IAPR International Conference on Pattern Recognition (ICPR2010) 2010.8

Experimental study on estimating traffic sign visibility in real environments

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

Tokai-Section Joint Conference on Electrical and Related Engineering 2010 2010.8

Quantification of the Visibility of Pedestrians Considering Objects' Saliency

Masashi Wakayama, Keisuke Doman, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

Tokai-Section Joint Conference on Electrical and Related Engineering 2010 2010.8

Study on Driving Behavior Prediction from Gaze Direction

Tatsuki Kamisaka, Masafumi Noda, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical and Related Engineering 2010 2010.8

Study on the Creation of a Scenery Category Map using Geo-tagged Images

Jiani Wang, Masafumi Noda, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Tokai-Section Joint Conference on Electrical and Related Engineering 2010 2010.8

Transition between Object Appearances Using Local VTM

Tomokazu Takahashi, Yuki Kono, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

13th Meeting on Image Recognition & Understanding (MIRU2010) 2010.7.1

映像認識と視線検出に着目した安全技術

出口大輔

運転行動の大規模計測と理解に関する国際シンポジウム - ググる時代の安全技術- 2010.7

A study on a construction of an adaptive traffic sign detector for various environments by combining multiple color features

Daisuke Deguchi, Keisuke Doman, Ichiro Ide, Hiroshi Murase

13th Meeting on Image Recognition & Understanding (MIRU2010) 2010.7

Detection of General Obstacles on the Road by Subtraction with Past In-Vehicle Camera Images

Haruya Kyutoku, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

13th Meeting on Image Recognition & Understanding (MIRU2010) 2010.7

Ego-localization by Sequantial Matching of Road-surface in Aerial Image and In-vehicle Camera Images

Masafumi Noda, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Yoshiko Kojima, Takashi Naito

13th Meeting on Image Recognition & Understanding (MIRU2010) 2010.7

Estimation of traffic sign visibility based on integration of \\multiple image features

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

13th Meeting on Image Recognition & Understanding (MIRU2010) 2010.7

Generation of an In-vehicle Camera Image Sequence without Moving Objects by Selection of Partial Images from Multiple Image Sequences

Hiroyuki Uchiyama, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

13th Meeting on Image Recognition & Understanding (MIRU2010) 2010.7

mediaWalker II: A news video archive browsing interface associated with Web contents (in Japanese)

Ichiro Ide, Tomokazu Takahashi, Tomoyoshi Kinoshita, Tomoki Okuoka, Daisuke Deguchi, Shinichi Satoh, Hiroshi Murase

13th Meeting on Image Recognition & Understanding (MIRU2010) 2010.7

Adaptive Feature Selection for Matching of Human in a Room Entrance

Takuya Honda, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

16th Symposium on Sensing via Image Information (SSII2010) 2010.6

Detection of On-the-spot Comments for Twitter

Takashi Kobayashi, Masafumi Noda, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2010.6

Estimation of Traffic Sign Visibility Toward Smart Driver Assistance International conference

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

2010 IEEE Intelligent Vehicles Symposium (IV2010) 2010.6

A study on a method to quantify the visibility of pedestrians considering saliency

Masashi Wakayama, Keisuke Doman, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

2010 IEICE General Conference 2010.3

Detection of Inconsistency between Face and Speaker based on the Co-occurrence of Lip Motion and Audio Features

Shogo Kumagai, Keisuke Doman, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2010.5

Scene Classification of Wedding Video Using Visual Features and Audio Features

Kazuki Sawai, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (MVE) 2010.5

HOG特徴を用いた映像中の人物の周期的動作検出に関する検討

久原卓, 出口大輔, 井手一郎, 村瀬洋

電子情報通信学会総合大会 2010.3

Wikipediaエントリを用いたニュース字幕中の人物の名寄せ

鈴木規之, 奥岡知樹, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

電子情報通信学会総合大会 2010.3

カメラとジャイロセンサを組み合わせた高精度な姿勢推定

小堀訓成, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

動的画像処理実利用化ワークショップ(DIA) 2010.3

ニュース映像間の意味構造を利用したWikipedia情報の拡張

奥岡知樹, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

情報処理学会全国大会 2010.3

ニュース映像間の時系列意味構造を利用したWikipedia記事のマルチメディア化

奥岡知樹, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

マルチメディア・仮想環境基礎研究会(MVE) 2010.3

フレーム選択型超解像処理を用いた低解像度文字認識手法の提案

大倉直, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

パターン認識・メディア理解研究会(PRMU) 2010.3

動画像を用いた一般物体のカテゴリ識別に関する検討

中村彰吾, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

電子情報通信学会総合大会 2010.3

料理レシピをわかりやすくするための理解困難な表現の補足

志土地由香, 出口大輔, 高橋友和, 井手一郎, 中村裕一, 村瀬洋

マルチメディア・仮想環境基礎研究会(MVE) 2010.3

注視対象の位置関係を利用した車載視線計測システム自動較正の高度化

山城賢二, 出口大輔, 高橋友和, 井手一郎, 村瀬洋, 樋口和則, 内藤貴志

パターン認識・メディア理解研究会(PRMU) 2010.3

猫パーツの抽出とその組み合わせによる猫の顔検出の高精度化

草野孝幸, 出口大輔, 井手一郎, 村瀬洋

動的画像処理実利用化ワークショップ(DIA) 2010.3

超解像を用いた低解像度QRコード画像認識の検討

加藤祐二, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

電子情報通信学会総合大会 2010.3

過去の車載カメラ映像との道路面差分による不特定障害物の検出

久徳遙矢, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋

パターン認識・メディア理解研究会(PRMU) 2010.3

CUDAプログラミング演習はじめてのCUDA

出口大輔, 二村幸孝

名古屋GPUコンピューティングセミナー 2009.12

オープンソースは時代の流れ!?

出口大輔

日本医用画像工学会大会 2009.8

局所濃淡構造解析に基づく3次元胸部CT像からの気管支領域抽出手法に関する検討

矢野裕章, 出口大輔, フォイヤーシュタインマルコ, 森健策, 北坂孝幸, 末永康仁

日本医用画像工学会大会 2009.8

Low-resolution Character Recognition by Video-based Super-resolution International conference

大倉直, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

International Conference on Document Analysis and Recognition (ICDAR) 2009.7

Scene Context 記述法の高度化による物体検出の性能向上

神谷保徳, 出口大輔, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2009.7

カメラとジャイロセンサを組み合わせた移動ロボットの高精度な姿勢推定

小堀訓成, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2009.7

市街地映像マップと2台の車載カメラを用いた自車位置推定

内山寛之, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2009.7

色変動を考慮した生成型学習による道路標識検出器の構築

道満恵介, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2009.7

車両の姿勢・速度情報を利用した車載カメラ画像からの路面標示認識

野田雅文, 高橋友和, 出口大輔, 井手一郎, 村瀬洋, 小島祥子, 内藤貴志

画像の認識・理解シンポジウム(MIRU) 2009.7

車載カメラ映像からの学習サンプルの自動収集による標識検出器の構築

出口大輔, 道満恵介, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2009.7

車載カメラ映像の道路面経時差分による前方障害物検出

久徳遙矢, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2009.7

View Hallucination: 大量の顔画像を用いた自由な視点からの顔画像の推定

高橋友和, 河野雄紀, 出口大輔, 井手一郎, 村瀬洋

Visual Computing/グラフィクスとCAD合同シンポジウム 2009.6.1

GPUによる高速画像処理～実例でわかるGPGPU～

出口大輔

画像センシングシンポジウム(SSII) 2009.6

Wikipediaを利用したニュース映像アーカイブへの自動索引付け

奥岡知樹, 高橋友和, 出口大輔, 井手一郎, 村瀬洋

デジタルコンテンツシンポジウム 2009.6

実世界シナリオに基づく大量映像の自動再編簒

井手一郎, 出口大輔, 村瀬洋, 高橋友和

科研「情報爆発IT基盤」シンポジウム 2009.6

過去の車載カメラ映像との道路面差分による前方障害物の検出

久徳遙矢, 出口大輔, 高橋友和, 井手一郎, 目加田慶人, 村瀬洋

画像センシングシンポジウム(SSII) 2009.6

SIFT Feature-based Motion Estimation for Bronchoscope Tracking

羅雄彪, フォイヤーシュタインマルコ, 出口大輔, 北坂孝幸, 末永康仁, 今泉和良, 長谷川好規, 森健策

日本医用画像工学会大会 2009.8

Automatic Calibration of an In-vehicle Gaze Tracking System Using Driver's Typical Gaze Behavior International conference

Kenji Yamashiro, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase, Kazunori Higuchi, Takashi Naito

2009 IEEE Intelligent Vehicles Symposium (IV2009) 2009.6

Ego-localization using Streetscape Image Sequences from In-vehicle Cameras International conference

Hiroyuki Uchiyama, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

2009 IEEE Intelligent Vehicles Symposium (IV2009) 2009.6

Recognition of Road Markings from In-Vehicle Camera Images by a Generative Learning Method International conference

Masafumi Noda, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Yoshiko Kojima, Takashi Naito

IAPR Conference on Machine Vision Applications (MVA) 2009 2009.5

A study on a Method for Estimation of Frontal Face from Two Face Images

Yuki Kono, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

2009 IEICE General Conference 2009.3.1

A Study on Matching of Human with Color Features for Entry Analysis

Takuya Honda, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

2009 IEICE General Conference 2009.3

A Study on a Method of Backward Tracking to Obtain Various Traffic Signs from In-Vehicle Camera Images

Daisuke Deguchi, Keisuke Doman, Ichiro Ide, Hiroshi Murase

2009 IEICE General Conference 2009.3

A Study on the Extraction of Descriptive Expressions in Cooking Recipes

Yuka Shidochi, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

2009 IEICE General Conference 2009.3

A preliminary study on a method for cats' face detection by utilizing local features

Takayuki Kusano, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2009 IEICE General Conference 2009.3

Classification of Near-Duplicate Video Segments in Broadcast Video by Occurence Patterns

Yuji Shamoto, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2009.3

A method for accelerating bronchoscope tracking based on image registration by using GPU International conference

Takamasa Sugiura, Daisuke Deguchi, Marco Feuerstein, Takayuki Kitasaka, Yasuhito Suenaga, Kensaku Mori

SPIE Medical Imaging 2009 2009.2

Automatic mediastinal lymph node detection in chest CT International conference

Marco Feuerstein, Daisuke Deguchi, Takayuki Kitasaka, Shingo Iwano, Kazuyoshi Imaizumi, Yoshinori Hasegawa, Yasuhito Suenaga, Kensaku Mori

SPIE Medical Imaging 2009 2009.2

気管支鏡ガイダンスシステムのための自動気管支構造認識手法の開発

太田峻輔, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 長谷川好規, 今泉和良, 高畠博嗣, 森雅樹, 名取博

医用画像研究会(MI) 2009.1

An improved method for automated recognition of bronchial tree structure by optimizing combinations of candidate anatomical names International conference

Takayuki Kitasaka, Shunsuke Ota, Daisuke Deguchi, Kensaku Mori, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi, Shingo Iwano, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

International Journal of Computer Assisted Radiology and Surgery 2009.6

若手が国際的に活躍するために（仮題）

玉木徹, 植松裕子, 近藤一晃, 酒井智弥, 島田敬士, 出口大輔, 山下隆義

パターン認識・メディア理解研究会(PRMU) 2009.12

Construction of cascaded traffic sign detector using generative learning International conference

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

4th International Conference on Innovative Computing, Information and Control (ICICIC2009) 2009.12

Labeling News Topic Threads with Wikipedia Entries International conference

Tomoki Okuoka, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

1st International Workshop on Content-Based Audio/Video Analysis for Novel TV Services (CBTV2009) 2009.12

多数の顔画像を用いて顔向きの変換を行うView hallucinationの提案

河野雄紀, 高橋友和, 出口大輔, 井手一郎, 村瀬洋

パターン認識・メディア理解研究会(PRMU) 2009.11.1

料理レシピ中の初心者に理解困難な表現の抽出

志土地由香, 出口大輔, 高橋友和, 井手一郎, 中村裕一, 村瀬洋

マルチメディア・仮想環境基礎研究会(MVE) 2009.11

空撮画像と時系列車載カメラ画像との照合による自車位置推定

野田雅文, 高橋友和, 出口大輔, 井手一郎, 村瀬洋, 小島祥子, 内藤貴志

パターン認識・メディア理解研究会(PRMU) 2009.11

複数映像統合による車載カメラ映像からの移動物体除去

内山寛之, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

パターン認識・メディア理解研究会(PRMU) 2009.11

車載カメラを用いた道路標識の視認性推定のための画像特徴の検討

道満恵介, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋, 玉津幸政

パターン認識・メディア理解研究会(PRMU) 2009.11

View Hallucinationを用いた顔画像推定におけるパッチサイズに関する検討

河野雄紀, 高橋友和, 出口大輔, 井手一郎, 村瀬洋

電気関係学会東海支部連合大会 2009.9.1

GPUによる高速画像処理

出口大輔, 井手一郎, 村瀬洋

画像応用技術専門委員会 2009.9

人物存在確率マップを用いた車載カメラ映像からの歩行者検出の検討

浜田大輔, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋

電気関係学会東海支部連合大会 2009.9

放送映像からの地名別風景ショットの抽出

王佳妮, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

電気関係学会東海支部連合大会 2009.9

空撮画像と車載カメラ画像の照合による自車位置推定の検討

野田雅文, 高橋友和, 出口大輔, 井手一郎, 村瀬洋, 小島祥子, 内藤貴志

電気関係学会東海支部連合大会 2009.9

複数映像統合による車載カメラからの移動物体除去手法の検討

内山寛之, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

電気関係学会東海支部連合大会 2009.9

頭部パーツの位置関係を考慮した猫の顔検出手法に関する検討

草野孝幸, 出口大輔, 井手一郎, 村瀬洋

電気関係学会東海支部連合大会 2009.9

Automated Anatomical Labeling of Bronchial Branches Extracted from CT Datasets Based on Machine Learning and Combination Optimization and Its Application to Bronchoscope Guidance International conference

Kensaku Mori, Shunsuke Ota, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Shingo Iwano, Yoshinori Hasegawa, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

12th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2009) 2009.9

Event date： 2009

Language：English Presentation type：Poster presentation

This paper presents a method for the automated anatomical labeling of bronchial branches extracted from 3D CT images based on machine learning and combination optimization. We also show applications of anatomical labeling on a bronchoscopy guidance system. This paper performs automated labeling by using machine learning and combination optimization. The actual procedure consists of four steps: (a) extraction of tree structures of the bronchus regions extracted from CT images, (b) construction of AdaBoost classifiers, (c) computation of candidate names for all branches by using the classifiers, (d) selection of best combination of anatomical names. We applied the proposed method to 90 cases of 3D CT datasets. The experimental results showed that the proposed method can assign correct anatomical names to 86.9% of the bronchial branches up to the sub-segmental lobe branches. Also, we overlaid the anatomical names of bronchial branches on real bronchoscopic views to guide real bronchoscopy.

DOI： 10.1007/978-3-642-04271-3_86

Cascaded Traffic Sign Detector Using Generative Learning Considering Color Variance

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2008.12

Ego-localization by Matching between Streetscape Image Sequence and Image Sequences from Two In-vehicle Cameras

Hiroyuki Uchiyama, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2008.12

PLUTO: A Common CAD Platform for Multiorgan Multidisease CAD (MoMd-CAD) International conference

Yukitaka Nimura, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga

RSNA (Radiological Society of North America) Scientific Assembly and Annual Meeting Program 2008 2008.11

CT値分布特徴を用いた3次元胸部CT像からの気管支領域抽出手法の検討

矢野裕章, 出口大輔, フォイヤーシュタインマルコ, 北坂孝幸, 森健策, 末永康仁

日本コンピュータ外科学会 2008.10

GPUを用いた気管支鏡カメラ動き推定処理の高速化に関する検討

杉浦貴優, 出口大輔, フォイヤーシュタインマルコ, 北坂孝幸, 森健策, 末永康仁, 今泉和良, 長谷川好規

日本コンピュータ外科学会 2008.10

気管支鏡追跡のため気管支鏡像特徴点抽出に関する研究

羅雄彪, フォイヤーシュタインマルコ, 出口大輔, 北坂孝幸, 末永康仁, 今泉和良, 長谷川好規, 森健策

日本コンピュータ外科学会 2008.10

造影胸部CT画像からの縦隔リンパ節の自動検出

フォイヤーシュタインマルコ, 出口大輔, 北坂孝幸, 岩野信吾, 今泉和良, 長谷川好規, 末永康仁, 森健策

日本コンピュータ外科学会 2008.10

CT値分布特徴を用いた3次元胸部CT像からの気管支領域内画素抽出法の検討

矢野裕章, 出口大輔, 北坂孝幸, 森健策, 末永康仁

電気関係学会東海支部連合大会 2008.9

A Method for Accelerating Bronchoscope Tracking Based on Image Registration by GPGPU International conference

Takamasa Sugiura, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga

International Workshop on Augmented environments for Medical Imaging and Computer-aided Surgery (AMI-ARCS) 2008 2008.9

Improvement of Accuracy of Marker-Free Bronchoscope Tracking Using Electromagnetic Tracker Based on Bronchial Branch Information International conference

Kensaku Mori, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi, Hirotsugu Takabatake

11th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2008) 2008.9

GPUを用いた気管支鏡カメラ動き推定処理の高速化

杉浦貴優, 出口大輔, 北坂孝幸, 森健策, 末永康仁

日本医用画像工学会大会 2008.8

GPUを用いた気管支鏡カメラ動き推定処理の高速化

杉浦貴優, 出口大輔, 北坂孝幸, 森健策, 末永康仁

日本VR医学会 2008.8

仮想呼吸動に対するマーカレス気管支鏡追跡手法の性能評価

出口大輔, 石谷和愛, 北坂孝幸, 森健策, 末永康仁, 今泉和良, 長谷川好規

日本医用画像工学会大会 2008.8

Augmented display of anatomical names of bronchial branches for bronchoscopy assistance International conference

Shunsuke Ota, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

4th International Workshop on Medical Imaging and Augmented Reality (MIAR2008) 2008.8

Development of a Common Platform for Computer-Aided Diagnosis of Medical Images

Yukitaka Nimura, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga

2008.8

An improved method for bronchoscope tracking using an electromagnetic tracker without fiducial markers International conference

Daisuke Deguchi, Kazuyoshi Ishitani, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi

22st International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2008) 2008.6

Automated anatomical labeling of bronchaial branches using multiple classifiers and its application to bronchoscopy guidance International conference

Shunsuke Ota, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

22st International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2008) 2008.6

Fiducial-free bronchoscope tracking using ultra-tiny electromagnetic tracker based on non-rigid transformation technique International conference

Kensaku Mori, Kazuyoshi Ishitani, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi

22st International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2008) 2008.6

GPU を利用した局所濃淡構造解析の高速化に関する検討

二村幸孝, 森直史, 出口大輔, 北坂孝幸, 森健策, 末永康仁

医用画像研究会(MI) 2008.5

Automated anatomical labeling of bronchial branches using multiple classifiers and its application to bronchoscopy guidance based on fusion of virtual and real bronchoscopy International conference

Shunsuke Ota, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

SPIE Medical Imaging 2008 2008.2

気管支の変形に対応したマーカレス気管支鏡位置追跡手法に関する検討

石谷和愛, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 今泉和良, 長谷川好規

医用画像研究会(MI) 2008.1

A study on an improved method for bronchoscope tracking \\using an electromagnetic tracker without fiducial markers

Daisuke Deguchi, Kazuyoshi Ishitani, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Kazuyoshi Imaizumi, Yoshinori Hasegawa

IEICE Technical Report (MI) 2008.1

気管支鏡ナビゲーションシステムのための磁気式位置センサと気管支鏡カメラの対応付け手法に関する検討

石谷和愛, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 今泉和良, 長谷川好規

日本コンピュータ外科学会 2007.11

複数の識別器の利用による気管支枝名自動対応付け手法に関する検討

太田峻輔, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 長谷川好規, 今泉和良, 高畠博嗣, 森雅樹, 名取博

コンピュータ支援画像診断学会大会 2007.11

An improved method for bronchoscope tracking using an electromagnetic tracker without fiducial markers

Daisuke Deguchi, Kazuyoshi Ishitani, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Kazuyoshi Imaizumi, Yoshinori Hasegawa

2007.11

Bronchoscope Tracking Without Fiducial Markers Using Ultra-tiny Electromagnetic Tracking System and Its Evaluation in Different Environments International conference

Kensaku Mori, Daisuke Deguchi, Kazuyoshi Ishitani, Takayuki Kitasaka, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi, Hirotsugu Takabatake

10th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2007) 2007.10

A method for bronchoscope tracking using position sensor without fiducial markers International conference

Daisuke Deguchi, Kazuyoshi Ishitani, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Yoshinori Hasegawa, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

21st International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2007) 2007.6

分岐特徴を利用した気管支鏡誘導システムのための観察部位特定手法の改善

篠原里代子, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 高畠博嗣, 森雅樹, 名取博

パターン認識・メディア理解研究会(PRMU) 2007.3

A method for bronchoscope tracking using position sensor without fiducial markers International conference

Daisuke Deguchi, Kazuyoshi Ishitani, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

SPIE Medical Imaging 2007 2007.2

Compensation of Electromagnetic trackintg system using an optical tracker and its application to bronchoscopy navigation system International conference

Kensaku Mori, Kazuyoshi Ishitani, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

SPIE Medical Imaging 2007 2007.2

Easy and stable bronchoscope camera calibration technique for bronchoscope navigation system International conference

Kazuyoshi Ishitani, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

SPIE Medical Imaging 2007 2007.2

3次元並列型画像処理ライブラリの構築とその性能評価

平野靖, 出口大輔, 高橋友和, 北坂孝幸, 伊藤文彦, 森健策, 萩原兼一, 末永康仁

コンピュータ支援画像診断学会大会 2006.10

固有空間画像照合法を用いた気管支鏡ナビゲーションのための観察部位識別法に関する検討

篠原里代子, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 高畠博嗣, 森雅樹, 名取博

パターン認識・メディア理解研究会(PRMU) 2006.3

Branch identification method for CT-guided bronchoscopy based on eigenspace image matching between real and virtual bronchoscopic images International conference

Riyoko Shinohara, Kensaku Mori, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

SPIE Medical Imaging 2006 2006.2

A preliminary study on introduction of a magnetic tracking sensor for bronchoscope navigation system International conference

Kazuyoshi Ishitani, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

International Workshop on Augmented environments for Medical Imaging and Computer-aided Surgery (AMI-ARCS) 2006 2006.10

多臓器・多疾病のための統合型ソフトウェアフレームワークの開発

二村幸孝, 出口大輔, 北坂孝幸, 森健策, 末永康仁

コンピュータ支援画像診断学会大会 2006.10

早期相と晩期相の3次元CT像を用いた肝細胞がん検出手法の開発

林雄一郎, 出口大輔, 北坂孝幸, 森健策, 目加田慶人, 末永康仁, 長谷川純一, 鳥脇純一郎

コンピュータ支援画像診断学会大会 2006.10

気管支鏡誘導システムのための固有空間画像照合法を用いた気管支鏡観察部位推定法に関する検討

篠原里代子, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 高畠博嗣, 森雅樹, 名取博

日本コンピュータ外科学会 2006.10

簡便な気管支鏡カメラキャリブレーション手法に関する検討

石谷和愛, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 高畠博嗣, 森雅樹, 名取博

日本コンピュータ外科学会 2006.10

A method for bronchoscope tracking using a ultra-tiny electromagnetic tracker without fiducial markers

Daisuke Deguchi, Kazuyoshi Ishitani, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

2006.10

画像間位置合わせ処理を利用した気管支鏡ナビゲーションシステムの開発

森健策, 北坂孝幸, 出口大輔, 高畠博嗣, 森雅樹, 名取博, 末永康仁

日本呼吸器内視鏡学会 2006.5

Bronchoscope Tracking Based on Image Registration Using Multiple Initial Starting Points Estimated by Motion Prediction International conference

Kensaku Mori, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Calvin R. Maurer Jr.

9th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2006) 2006.10

2時相の3次元CT像を用いた肝臓がん検出手法に関する検討

林雄一郎, 出口大輔, 北坂孝幸, 森健策, 目加田慶人, 末永康仁, 鳥脇純一郎, 縄野繁

医用画像研究会(MI) 2006.9

多時相CT像からの肝臓がん抽出手法の開発

林雄一郎, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 目加田慶人, 鳥脇純一郎

電気関係学会東海支部連合大会 2006.9

多臓器・多疾病コンピュータ支援診断システムの開発

二村幸孝, 出口大輔, 北坂孝幸, 森健策, 末永康仁

電気関係学会東海支部連合大会 2006.9

気管支鏡ナビゲーションシステムにおける磁気式位置センサ補正法に関する検討

石谷和愛, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 高畠博嗣, 森雅樹, 名取博

電気関係学会東海支部連合大会 2006.9

気管支鏡ナビゲーションシステムにおける簡便なカメラキャリブレーション手法に関する検討

石谷和愛, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 高畠博嗣, 森雅樹, 名取博

医用画像研究会(MI) 2006.9

A study on a method for bronchoscope tracking using positional sensor without fiducial markers

Daisuke Deguchi, Kazuyoshi Ishitani, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

IEICE Technical Report (MI) 2006.9

CT値分布推定を用いた4時相腹部3次元CT像からの複数臓器領域の抽出

坂下牧子, 出口大輔, 北坂孝幸, 森健策, 末永康仁

日本医用画像工学会大会 2006.7

CT値分布推定を用いた4時相腹部3次元CT像からの複数臓器領域の抽出手法

坂下牧子, 出口大輔, 北坂孝幸, 森健策, 末永康仁

医用画像研究会(MI) 2006.7

多臓器・多疾病を対象とする統合型診断支援システムの開発

二村幸孝, 出口大輔, 北坂孝幸, 森健策, 末永康仁

日本医用画像工学会大会 2006.7

気管支鏡ナビゲーションシステムにおける磁気式位置センサ導入に関する検討

石谷和愛, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 高畠博嗣, 森雅樹, 名取博

日本医用画像工学会大会 2006.7

Detection of liver cancer regions from dynamic CT images International conference

Yuichiro Hayashi, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yoshito Mekada, Yasuhito Suenaga

20th International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2006) 2006.6

Image-based bronchoscope tracking using motion predication and multiple searches International conference

Kensaku Mori, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

20th International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2006) 2006.6

マイクロCT画像を用いた肺微細構造の解析および雑音除去手法の検討

佐藤嘉晃, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 鳥脇純一郎, 高畠博嗣, 森雅樹, 名取博

コンピュータ支援画像診断学会大会 2005.11

An improvement of bronchoscope tracking by detecting obscured images

Daisuke Deguchi, Riyoko Shinohara, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Jun-ichi Hasegawa, Junichiro Toriwaki, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

2005.7

A method for bronchoscope tracking by combining a position sensor and image registration International conference

Daisuke Deguchi, Kenta Akiyama, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Jun-ichi Hasegawa, Junichiro Toriwaki, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

19th International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2005) 2005.6

Real BronschoscopyとVirtualized Bronchoscopyの融合による気管支鏡ナビケーション

森健策, 北坂孝幸, 出口大輔, 末永康仁

日本呼吸器内視鏡学会 2005.5

複数時相CT像からのCT値分布推定を用いた肝臓領域抽出手法

松岡寿典, 出口大輔, 林雄一郎, 北坂孝幸, 森健策, 目加田慶人, 末永康仁, 長谷川純一, 鳥脇純一郎

日本生体医工学会 2005.4

イメージレジストレーションと位置センサを用いた気管支鏡動き推定手法の改善

秋山健太, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 長谷川純一, 鳥脇純一郎, 高畠博嗣, 森雅樹, 名取博

パターン認識・メディア理解研究会(PRMU) 2005.3

早期相・晩期相からのCT値分布推定による肝臓領域抽出手法の開発

林雄一郎, 出口大輔, 松岡寿典, 北坂孝幸, 森健策, 目加田慶人, 末永康仁, 長谷川純一, 鳥脇純一郎

医用画像研究会(MI) 2005.1

A study on bronchoscope tracking by combining a positional sensor and image registration

Daisuke Deguchi, Kenta Akiyama, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Jun-ichi Hasegawa, Junichiro Toriwaki, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

IEICE Technical Report (MI) 2005.1

肺標本のマイクロCT画像からの肺胞領域抽出手法に関する検討

佐藤嘉晃, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 鳥脇純一郎, 高畠博嗣, 森雅樹, 名取博

電気関係学会東海支部連合大会 2005.9

多臓器・多疾病を対象とする統合型コンピュータ支援画像診断システムの開発

二村幸孝, 出口大輔, 北坂孝幸, 森健策, 末永康仁

コンピュータ支援画像診断学会大会 2005.11

早期相と晩期相を用いた肝細胞がん検出に関する検討

林雄一郎, 出口大輔, 目加田慶人, 北坂孝幸, 森健策, 末永康仁, 鳥脇純一郎

コンピュータ支援画像診断学会大会 2005.11

An improvement of bronchoscope tracking by detecting bubble image

Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Junichiro Toriwaki, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

2005.11

Hybrid Bronchoscope Tracking Using a Magnetic Tracking Sensor and Image Registration International conference

Kensaku Mori, Daisuke Deguchi, Kenta Akiyama, Takayuki Kitasaka, Calvin R. Maurer Jr., Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

8th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2005) 2005.10

磁気式位置センサを用いた気管支内視鏡ナビゲーションに関する予備的検討

秋山健太, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 鳥脇純一郎, 名取博, 高畠博嗣, 森雅樹

日本コンピュータ外科学会 2004.12

A study on a method for automated liver region extraction by analyzing CT value distributions from multi-phase CT images

Daisuke Deguchi, Yuichiro Hayashi, Kensaku Mori, Yoshito Mekada, Yasuhito Suenaga, Jun-ichi Hasegawa, Junichiro Toriwaki

2004.12

超小型磁気式位置センサを用いた気管支内視鏡ナビゲーションに関する検討

秋山健太, 出口大輔, 北坂孝幸, 森健策, 末永康仁

電気関係学会東海支部連合大会 2004.9

Fast and Accurate Bronchoscope Tracking using Image Registration and Motion Prediction International conference

Jiro Nagao, Kensaku Mori, Tsutomu Enjoji, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Jun-ichi Hasegawa, Junichiro Toriwaki, Hirotsugu Takabatake, Hiroshi Natori

7th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2004) 2004.9

Improved camera-tracking method by combining motion prediction and image registration for bronchoscope navigation system International conference

Kensaku Mori, Tsutomu Enjoji, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Junichiro Toriwaki, Hiroshi Natori, Hirotsugu Takabatake

18th International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2004) 2004.6

Evaluation of a virtual needle biopsy system based on resected specimens of prostate

Norishige Fukushima, Daisuke Deguchi, Yoshito Mekada, Kensaku Mori, Hiroshi Murase, Junichiro Toriwaki, Masanori Noguchi

IEICE Technical Report (MI) 2004.5

New image similarity measures for bronchoscope tracking based on image registration between virtual and real bronchoscopic images International conference

Kensaku Mori, Tsutomu Enjoji, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Junichiro Toriwaki, Hirotsugu Takabatake, Hiroshi Natori

SPIE Medical Imaging 2004 2004.2

A method for bronchoscope tracking by using image registration and motion prediction

Daisuke Deguchi, Tsutomu Enjoji, Kensaku Mori, Yasuhito Suenaga, Jun-ichi Hasegawa, Junichiro Toriwaki, Hirotsugu Takabatake, Hiroshi Natori

IEICE Technical Report (MI) 2004.1

Development of a method for automated liver region extraction from contrasted 3D abdominal X-ray CT images

Yuichiro Hayashi, Daisuke Deguchi, Kensaku Mori, Yoshito Mekada, Junichiro Toriwaki

IEICE Technical Report (MI) 2004.1

気管支鏡カメラ動き推定における画像間類似度の比較・検討

圓城寺努, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 長谷川純一, 鳥脇純一郎

コンピュータ支援画像診断学会大会 2003.12

Development of a method for automated liver region extraction by analyzing distribution of CT values from 3D abdominal X-ray CT images

Daisuke Deguchi, Yuichiro Hayashi, Kensaku Mori, Yoshito Mekada, Junichiro Toriwaki

2003.12

New Image Similarity Measure for Bronchoscope Tracking Based on Image Registration International conference

Daisuke Deguchi, Kensaku Mori, Yasuhito Suenaga, Jun-ichi Hasegawa, Junichiro Toriwaki, Hirotsugu Takabatake, Hiroshi Natori

6th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2003) 2003.11

前立腺仮想針生検による穿刺条件の評価

出口大輔, 目加田慶人, 村瀬洋, 長谷川純一, 鳥脇純一郎, 野口正典

日本エム・イー学会東海支部学術集会 2003.10

気管支内視鏡カメラの動き推定処理における新しい画像間類似度計算法の提案とその評価

圓城寺努, 出口大輔, 北坂孝幸, 森健策, 末永康仁, 長谷川純一, 鳥脇純一郎

電気関係学会東海支部連合大会 2003.10

情報増強バーチャルエンドスコピー、in シンポジウム:手術シミュレーションと術中イメージングナビゲーション

鳥脇純一郎, 森健策, 林雄一郎, 出口大輔

日本外科系連合学会 2003.6

New calculation method of image similarity for endoscope tracking based on image registration in endoscope navigation International conference

Daisuke Deguchi, Kensaku Mori, Yasuhito Suenaga, Jun-ichi Hasegawa, Junichiro Toriwaki, Hiroshi Natori, Hirotsugu Takabatake

17th International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2003) 2003.6

A virtual needle biopsy for the virtual prostate model based on anatomical knowledge

Shinya Kodama, Daisuke Deguchi, Kensaku Mori, Yoshito Mekada, Jun-ichi Hasegawa, Junichiro Toriwaki, Masanori Noguchi

IEICE Technical Report (MI) 2003.5.22

An improved method for calculating image similarity between virtual and real endoscopic images in tracking bronchoscope motion

Daisuke Deguchi, Kensaku Mori, Jun-ichi Hasegawa, Junichiro Toriwaki, Hiroshi Natori, Hirotsugu Takabatake

IEICE Technical Report (MI) 2003.1

仮想病変に対する前立腺針生検シミュレーションとその評価

出口大輔, 森健策, 目加田慶人, 長谷川純一, 鳥脇純一郎, 野口正典

コンピュータ支援画像診断学会大会 2002.11

Camera motion tracking of real bronchoscope using epipolar geometry analysis and CT derived bronchoscopic images International conference

Daisuke Deguchi, Kensaku Mori, Jun-ichi Hasegawa, Junichiro Toriwaki, Hirotsugu Takabatake, Hiroshi Natori

SPIE Medical Imaging 2002 2002.2

A preliminary study on a prostate biopsy simulation system based on images of resected prostate

Akihiro Yamaguchi, Daisuke Deguchi, Kensaku Mori, Yoshito Mekada, Junichiro Toriwaki, Masanori Noguchi

IEICE Technical Report (MI) 2002.4

Development of A Biopsy Simulation System for Prostate Cancers with Application to The Effectiveness Evaluation

Akihiro Yamaguchi, Daisuke Deguchi, Kensaku Mori, Yoshito Mekada, Junichiro Toriwaki, Masanori Noguchi

2002.5

A Method for Tracking Camera Motion of Real Endoscope by Using Optical Flow Analysis and Image-based Registration

Daisuke Deguchi, Kensaku Mori, Junichiro Toriwaki, Jun-ichi Hasegawa, Hiroshi Natori, Hirotsugu Takabatake

2001.11

A method for tracking the camera motion of real endoscope by epipolar geometry analysis and virtual endoscopy system International conference

Kensaku Mori, Daisuke Deguchi, Jun-ichi Hasegawa, Yasuhito Suenaga, Junichiro Toriwaki, Hirotsugu Takabatake, Hiroshi Natori

4th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2001 2001.10

A Method for Camera Motion Estimation of Real Endoscope Based on Optical Flow Analysis

Daisuke Deguchi, Kensaku Mori, Junichiro Toriwaki, Jun-ichi Hasegawa, Hirotsugu Takabatake, Hiroshi Natori

2001.7

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