研究者詳細 - 出口　大輔

論文 - 出口　大輔

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Semantic matters: A constrained approach for zero-shot video action recognition 査読有り

Zhenzhen Quan, Jialei Chen, Daisuke Deguchi, Jie Sun, Chenkai Zhang, Yujun Li, Hiroshi Murase

Pattern Recognition 162 巻頁： 111402 2025年6月

A Cross-Modal Knowledge Distillation Approach for RGB-to-Infrared Video Action Recognition 査読有り

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

Proceedings of Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2025) 2025年2月

Multi-group Vision Semantic Centroid for Semantic Segmentation 査読有り

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

Proceedings of Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2025) 2025年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

CROCODILE: Crop-based Contrastive Discriminative Learning for Enhancing Explainability of End-to-End Driving Models 査読有り

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

Proceedings of ACCV Workshop on Machine Learning and Computing for Visual Semantic Analysis (MLCSA2024) 頁： 378 - 393 2024年12月

Early prediction of At-risk students through Learning-Activity Forecasting 査読有り

Yuya Ozaki, Daisuke Deguchi, Haruya Kyutoku, Hiroshi Murase

Proceedings of 32nd International Conference on Computers in Education (ICCE2024) 2024年11月

Toward Explainable End-to-End Driving Models via Simplified Objectification Constraints 査読有り

Chenkai Zhang, Daisuke Deguchi, Jialei Chen, Hiroshi Murase

IEEE Transactions on Intelligent Transportation Systems 25 巻 ( 10 ) 頁： 14521 - 14534 2024年10月

記述言語：英語掲載種別：研究論文（学術雑誌）

The end-to-end driving models (E2EDMs) convert environmental information into driving actions using a complex transformation which makes E2EDMs have high prediction accuracy. Due to the black-box nature of transformation, the E2EDMs have low explainability. To solve this problem, explanation methods are used to generate explanations for observation. Based on current explanation methods, previous studies tried to further improve the explainability of E2EDMs by integrating an object detection module, however, these methods have many problems: Firstly, due to the requirement of the object detection module, they lack flexibility. Secondly, they neglect an essential property, i.e. , simplicity, to improve explainability. In this paper, since humans prefer object-level and simple explanations in driving tasks, we argue that explainability is decided by two properties which are the objectification degree (the extent to which driving related-object features are utilized) and simplification degree (the simplicity of the explanation), thus we propose Simplified Objectification Branches (SOB) to improve the explainability of E2EDMs. Firstly, this structure could be integrated into any existing E2EDMs and thus have high flexibility. Secondly, the SOB explicitly improves the simplification degree without sacrificing the objectification degree of the explanations. By designing several indicators, i.e. , heatmap satisfaction, driving action reproduction score, deception level, etc. , we proved that SOB could help E2EDMs generate better explanations. Notably, the SOB could also further enhance E2EDMs’ prediction accuracy.

DOI： 10.1109/TITS.2024.3385754

Frozen is better than learning: A new design of prototype-based classifier for semantic segmentation 査読有り

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

Pattern Recognition 152 巻 2024年8月

記述言語：英語掲載種別：研究論文（学術雑誌）

Semantic segmentation models comprise an encoder to extract features and a classifier for prediction. However, the learning of the classifier suffers from the ambiguity which is caused by two factors: (1) the weights of a classifier for similar categories may have positive similarities lowing the performance for similar categories, named correlation ambiguity, and (2) the classifier is prone to predict the category with a larger L2 norm and vice versa, termed prior ambiguity. To comedy the issues, we propose Category-Basis Prototype (CBP), frozen and mutually orthogonalized prototypes with equal L2 norm. Orthogonalization prevents the prototypes from being similar to each other and the equality decouples the prediction from the L2 norm. To better shape the feature space, we propose Online Centroid Contrastive Loss (OCCL) equipped with centroid and category- level losses. Experiments show that our method yields compelling results over two widely applied benchmarks indicating the effectiveness of our methods.

DOI： 10.1016/j.patcog.2024.110431

Eye-contact Transformer: シーンコンテクストを考慮し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

電子情報通信学会論文誌 J107-D 巻 ( 4 ) 頁： 231 - 242 2024年4月

記述言語：日本語掲載種別：研究論文（学術雑誌）

歩行者が自車に気づいているかどうかの判断は，安全に車両を運転する上でとても重要である．このような自車への気付きの判断において，歩行者とのアイコンタクトは重要な役割を担っている．従来，このようなアイコンタクト検出には眼球計測により得られる視線推定結果が広く用いられており，道路環境のように歩行者と車両の距離が遠く歩行者の眼球を高解像度に計測できない場合は適用できない．そこで本論文では，歩行者の骨格系列と周囲環境の特徴を統合利用することにより，複雑な交通環境であっても歩行者とのアイコンタクトを精度良く検出可能な手法を提案する．具体的には，歩行者の骨格系列と周囲環境の特徴間の関係性をTransformerベースのモデルで捉えるEye-contact Transformerを構築する．車載カメラ画像群に対してアイコンタクトのアノテーションを付与したデータセットを用いた実験により，提案手法の有効性を確認した．

DOI： 10.14923/transinfj.2023PDP0024

Centroid Module for Shaping Feature Space in Semantic Segmentation

Jialei Chen, Daisuke Deguchi, Chenkai Zhang, Hiroshi Murase

Proceedings of 3rd Asia Conference on Cloud Computing, Computer Vision and Image Processing (3CVIP 2024) 2024年3月

Subjective Baggage-Weight Estimation Based on Human Walking Behavior 査読有り

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

IEEE Access 12 巻頁： 39390 - 39398 2024年3月

Category-Level Object Pose Estimation in Heavily Cluttered Scenes by Generalized Two-Stage Shape Reconstructor 査読有り

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

IEEE Access 12 巻頁： 33440 - 33448 2024年3月

Comprehensive Evaluation of End-to-End Driving Model Explanations for Autonomous Vehicles 査読有り

Chenkai Zhang, Daisuke Deguchi, Jialei Chen, Hiroshi Murase

Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP) 2024 2 巻 ( 2184-4321 ) 頁： 509 - 518 2024年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Pedestrian's Gaze Object Detection in Traffic Scene 査読有り

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

Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP) 2024 2 巻頁： 333 - 340 2024年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Texture-guided transfer learning for low-quality face recognition 査読有り

Meng Zhang, Rujie Liu, Daisuke Deguchi, Hiroshi Murase

IEEE Transactions on Image Processing 2023年11月

記述言語：英語掲載種別：研究論文（学術雑誌）

Although many advanced works have achieved significant progress for face recognition with deep learning and large-scale face datasets, low-quality face recognition remains a challenging problem in real-word applications, especially for unconstrained surveillance scenes. We propose a texture-guided (TG) transfer learning approach under the knowledge distillation scheme to improve low-quality face recognition performance. Unlike existing methods in which distillation loss is built on forward propagation; e.g., the output logits and intermediate features, in this study, the backward propagation gradient texture is used. More specifically, the gradient texture of low-quality images is forced to be aligned to that of its high-quality counterpart to reduce the feature discrepancy between the high-and low-quality images. Moreover, attention is introduced to derive a soft-attention (SA) version of transfer learning, termed as SA-TG, to focus on informative regions. Experiments on the benchmark low-quality face DB’s TinyFace and QMUL-SurFace confirmed the superiority of the proposed method, especially more than 6.3% Rank1 accuracy improvement is achieved on TinyFace.

DOI： 10.1109/TIP.2023.3335830

Computational measurement of perceived pointiness from pronunciation 査読有り

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

Multimedia Tools and Applications 2023年8月

Refined Objectification for Improving End-to-End Driving Model Explanation Persuasibility 査読有り

Chenkai Zhang, Daisuke Deguchi, Hiroshi Murase

Proceedings of 2023 IEEE Intelligent Vehicles Symposium (IV2023) 2023年6月

観衆の顔向きの時空間統合による注目対象の位置及び被注目度の推定査読有り

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

電子情報通信学会論文誌 J106-A 巻 ( 3 ) 頁： 58 - 69 2023年3月

End-to-End gaze grounding from a person pictured from behind 査読有り

Hayato Yumiya, Daisuke Deguchi, Yasutomo Kawanishi, Hiroshi Murase

Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications 5 巻頁： 898 - 905 2023年2月

Subjective Baggage-Weight Estimation from Gait: Can You Estimate How Heavy the Person Feels? 査読有り

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

Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP) 2023 5 巻頁： 567 - 574 2023年2月

A Preliminary Study on View Independent Panoptic Scene Change Detection 査読有り

Jiaxin Li, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

Proceedings of International Workshop on Advanced Image Technology (IWAIT) 2023 2023年1月

More Persuasive Explanation Method for End-to-End Driving Models 査読有り

Chenkai Zhang, Daisuke Deguchi, Yuki Okafuji, Hiroshi Murase

IEEE Access 11 巻頁： 4270 - 4282 2023年1月

記述言語：英語掲載種別：研究論文（学術雑誌）

With the rapid development of autonomous driving technology, a variety of high-performance end-to-end driving models (E2EDMs) are being proposed. In order to understand the computational methods of E2EDMs, pixel-level explanations methods are used to obtain the explanations of the E2EDMs. However, little attention has been paid to the excellence of the explanations of E2EDMs. Therefore, in order to build trustworthy E2EDMs, we focus on improving the persuasibility of the explanations of E2EDMs. We propose an object-level explanation method (main approach) for E2EDMs, which masks the objects in the image and then treats the change in the prediction result as the importance of the objects, then we explain the E2EDM by the importance of each object. To further validate the effectiveness of object-level explanations, we propose another approach (validation approach), which trains E2EDMs with object information as input and generates the importance of objects using general explanation methods. Both approaches generate object-level explanations, in order to compare these object-level explanations with traditional pixel-level explanations, we propose experimental methods to measure the persuasibility of explanations of E2EDMs through a subjective and objective method. The subjective method evaluates persuasibility based on the extent to which participants think the importance of features indicated by the explanations is correct. The objective method evaluates the persuasibility based on the human annotation similarity between provided with only the important part of images and provided with the complete images. The experimental results show that the object-level explanations are more persuasive than the traditional pixel-level explanations.

DOI： 10.1109/ACCESS.2023.3235739

Analysis of Gaze while Viewing Videos at Various Playback Speeds 査読有り

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

Proceedings of the International Display Workshops 29 巻頁： 702 - 705 2022年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

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

Proceedings of the 18th IEEE International Conference on Advanced Video and Signal-Based Surveillance 頁： 1 - 7 2022年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

Detection of distant eye-contact using spatio-temporal pedestrian skeletons 査読有り

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

2022年9月

サラウンド映像視聴時の注視点分布の分析査読有り

高比良英朗, 篠原未歩, 野坂祐介, 横内雅也, 山田光穗, 平山高嗣, 川西康友, 出口大輔, 井手一郎, 村瀬洋

ヒューマンインタフェース学会論文誌 24 巻 ( 3 ) 頁： 195 - 204 2022年8月

記述言語：日本語掲載種別：研究論文（学術雑誌）

We have been conducting research focusing on the human gaze as a principal biological reaction while viewing videos. In this paper, we clarify the difference in the area of gaze region under different sound conditions; monaural (1.0 ch), stereo (2.0 ch), and surround (5.1 ch). We measured the gaze of subjects viewing video scenes of natural landscapes and calculated the horizontal and vertical standard deviations of the gaze points and the area of gaze region defined from them. A two-way analysis of variance shows the main effects of each of the sound and scene conditions on the vertical standard deviation of the gaze points and the interaction effect and the main effect of the sound condition on the area of gaze region. In addition, a multiple comparison test shows the significant differences in the vertical standard deviation for the interaction effect between the sound and scene conditions and in the area of gaze region for the sound conditions between monaural and stereo or surround. The hypothesis that the variance of gaze points is expanded by the surround sound is confirmed experimentally.

DOI： 10.11184/his.24.3_195

車両歩行者間のインタラクション行動のモデル化のための 2 段階入出力隠れマルコフモデル査読有り

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

情報処理学会論文誌 63 巻 ( 8 ) 頁： 1371 - 1382 2022年8月

記述言語：日本語掲載種別：研究論文（学術雑誌）

自動車と歩行者が交差するシーンに着目し，車両歩行者間のインタラクティブな行動をモデル化するための2段階入出力隠れマルコフモデル（TS-IOHMM）を提案する．従来の入出力隠れマルコフモデルは，相手の行動に依存して自己の意図と行動が決定される過程をモデル化した．提案するTS-IOHMMは，相手の行動の影響に加え，自己の行動もまた相手の意図に影響を与える点を考慮したモデルで，これまで注目されなかった意図と行動の変化にある法則性（ルール）の獲得を目指したモデルである．検証用に設定したルールに従って意図や行動が変化するシミュレーションデータを作成し，それを用いて提案モデルがどのようなルールを獲得できるか検証する実験を行った．その結果から，提案モデルがシミュレーションと同等の意図や行動を出力する行動ルールを獲得できたことを確認した．

DOI： 10.20729/00218987

Intuitive Gait Modeling using Mimetic-Words for Gait Description and Generation 査読有り

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

頁： 240 - 245 2022年8月

Context-Aware Contribution Estimation for Feature Aggregation in Video Face Recognition 査読有り

Meng Zhang, Rujie Liu, Daisuke Deguchi, Hiroshi Murase

IEEE Access 10 巻頁： 79301 - 79310 2022年7月

記述言語：英語掲載種別：研究論文（学術雑誌）

The difficulties in video-based face recognition, such as dramatic pose variations and low quality, can be alleviated by leveraging the rich complementary information between the frames. However, limited by the mini-batch training strategy, the current deep learning methods only utilizes the frames in each batch during training, which ignore the context of the entire video. In this paper, we propose a context-aware feature aggregation scheme to aggregate complementary information between different frames. Firstly, a two-branch structure is designed as the C ontext-aware feature A ggregation N etwork ( CAN ). Secondly, a context-aware training strategy using a context bank is proposed, which alleviates the limitation of mini-batch samples by using the context of the entire video or several images belonging to the same ID and thus achieves global contribution estimation result. Comparative studies on benchmark datasets, such as IJB-C, YouTube Face (YTF), PaSC and COX, confirm that the proposed approach can achieve state-of-the-art level. Meanwhile, qualitative analysis on Multi-PIE dataset indicates that the contribution learned by the CAN is reasonable and beneficial to video face recognition.

DOI： 10.1109/ACCESS.2022.3193787

SfM-student: SfM法を用いたデータ拡張による列車前方映像からのセマンティックセグメンテーション査読有り

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

電子情報通信学会論文誌 J105-A 巻 ( 4 ) 頁： 48 - 57 2022年4月

記述言語：日本語掲載種別：研究論文（学術雑誌）

重要な公共交通機関として広く社会に普及している鉄道の沿線には，信号機や踏切など列車の安全運行を支える多くの設備が設置されている．これらの設備の日常的な整備や設置状況などに関する情報収集業務の多くは人手により行われており，その維持管理作業の自動化・効率化を実現する技術が強く求められている．このような課題に対して，営業運転中の列車に搭載したカメラにより前方を撮影した列車前方映像のみを用い，セマンティックセグメンテーションを施すことで鉄道環境における沿線設備などを自動認識する技術に期待が寄せられている．しかし，セマンティックセグメンテーションでは画素単位でクラス情報を人手で付与した学習データが必要であり，高い性能を得るために必要な大量の学習データを用意するコストは非常に高い．そこで本論文では，教師なしデータに対するセマンティックセグメンテーション結果とStructure from Motion（SfM）法による3次元復元結果を組み合わせることによってラベル付き3次元点群を生成し，それらを画像平面に投影することで擬似的なデータ拡張を行うSfM-student法を提案する．これにより，限られたラベルあり学習データのみからセマンティックセグメンテーションの精度向上を図る．実際の鉄道環境で撮影したデータを用いた実験を行ったところ，提案する3次元情報を利用した擬似的なデータ拡張手法は既存のデータ拡張手法と比べてセマンティックセグメンテーション精度を向上させることを確認した．

DOI： 10.14923/transfunj.2021JAP1021

歩行者属性と運転スキルを考慮したリスクポテンシャル関数による歩行者に対する安全マージン予測査読有り

前川大和, 平山高嗣, 川西康友, 出口大輔, 劉海龍, 井手一郎, 村瀬洋

電子情報通信学会論文誌 J105-A 巻 ( 3 ) 頁： 38 - 42 2022年3月

記述言語：日本語掲載種別：研究論文（学術雑誌）

本論文では，電動車いすのより安全な自動運転のための経路計画を目的として，歩行者属性と運転スキルを考慮したリスクポテンシャル関数を運転データから推定する手法を提案し，それらによる歩行者に対する電動車いすの安全マージンの違いを明らかにする．

DOI： 10.14923/transfunj.2021JAL2005

Masked face recognition with mask transfer and self-attention under the COVID-19 pandemic 査読有り

Zhang Meng, Rujie Liu, Daisuke Deguchi, Hiroshi Murase

IEEE Access 10 巻頁： 20527 - 20538 2022年2月

記述言語：英語掲載種別：研究論文（学術雑誌）

Face masks bring a new challenge to face recognition systems especially against the background of the COVID-19 pandemic. In this paper, a method mitigating the negative effects of mask defects on face recognition is proposed. Firstly, a low-cost, accurate method of masked face synthesis, i.e. mask transfer, is proposed for data augmentation. Secondly, an attention-aware masked face recognition (AMaskNet) is proposed to improve the performance of masked face recognition, which includes two modules: a feature extractor and a contribution estimator. Therein, the contribution estimator is employed to learn the contribution of the feature elements, thus achieving refined feature representation by simple matrix multiplications. Meanwhile, the end-to-end training strategy is utilized to optimize the entire model. Finally, a mask-aware similarity matching strategy(MS) is taken to improve the performance in the inference stage. The experiments show that the proposed method consistently outperforms on three masked face recognition datasets: RMFRD [1], COX [2] and Public-IvS [3]. Meanwhile, qualitative analysis experiments using CAM [4] indicate that the contribution learned by AMaskNet is more conducive to masked face recognition.

DOI： 10.1109/ACCESS.2022.3150345

Active Learning for Human Pose Estimation based on Temporal Pose Continuity 査読有り

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

Proceedings of International Workshop on Advanced Image Technology (IWAIT) 2022 2022年1月

Soft-boundary label relaxation with class placement constraints for semantic segmentation of the railway environment 査読有り

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

Pattern Recognition Letters 150 巻頁： 258 - 264 2021年10月

Pointedness of an Image: Measuring How Pointy an Image is Perceived 査読有り

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

Proceedings of HCII 2021 37 巻頁： 137 - 144 2021年7月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

Best next-viewpoint recommendation by selecting minimum pose ambiguity for category-level object pose estimation 査読有り

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

Journal of the Japan Society for Precision Engineering 87 巻 ( 5 ) 頁： 440 - 446 2021年5月

画像特徴点の対応を制約とした疎なLiDAR点群からのOdometry推定査読有り

清水政行, 川西康友, 出口大輔, 井手一郎, 村瀬洋

精密工学会誌 87 巻 ( 5 ) 頁： 447 - 454 2021年5月

光線方向の違いを考慮したライトフィールド特徴量の提案査読有り

清水政行, 川西康友, 出口大輔, 井手一郎, 村瀬洋

精密工学会誌 87 巻 ( 2 ) 頁： 197 - 205 2021年2月

記述言語：日本語掲載種別：研究論文（学術雑誌）

Many camera and photo applications, for example image mosaicing, Simultaneous Localization And Mapping (SLAM), and so on, use image keypoints, descriptors, and their matching. Recently, obtaining light-field has become easier thanks to the commercialization of light-field cameras. Light-field is a record of not only light ray intensity but also directions, and multi-view images can be acquired with it. In this paper, a light-field descriptor with light ray directions using light-field is proposed. A light-field descriptor is defined as a set of feature vectors that change according to the direction of the light ray. In addition, a method to match these descriptors is proposed. As the method focuses on the direction of the light ray, it allows more accurate matching than a conventional method when the camera pose changes against the target. To confirm the effectiveness, the proposed method is evaluated by using light-field image recorded in a real scene. As a result, the proposed method is shown to improve the accuraccy over a conventional method. In particular, the closer the distance between the target and the camera, the better accuracy of the proposed method could be achieved.

DOI： 10.2493/jjspe.87.197

ColAtt-Net: In Reducing the Ambiguity of Pedestrian Orientations on Attribute-Aware Semantic Segmentation Task 査読有り

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

IEEJ Transactions on Electrical and Electronic Engineering 16 巻 ( 2 ) 頁： 295 - 306 2021年2月

記述言語：英語掲載種別：研究論文（学術雑誌）

Semantic segmentation has become one of the trending topics in the world of computer vision and deep learning. Recently, due to an increasing demand to solve a semantic segmentation task simultaneously with attribute recognition of objects, a new task named attribute-aware semantic segmentation has been introduced. Since the task requires to handle pixel-wise object class estimation with its attributes such as a pedestrian’s body orientation, previous works had difficulties to handle ambiguous attributes such as body orientations in object-level, especially when segmenting the pedestrians with their attributes correctly. This paper proposes the ColAtt-Net that is an attribute-aware semantic segmentation model augmented by a column-wise mask branch to predict the pedestrians’ orientations in the horizontal perspective of the input image. We firmly assume that the pedestrians captured by a car-mounted camera are distributed horizontally so that for each column of the input image, the pedestrian pixels can be labeled with one orientation uniformly. In the proposed method, we split the output of the base semantic segmentation model into two branches; one branch for segmenting the object categories, while the other one, as the novel column-wise attribute branch, is to map the recognition of pedestrian’s orientations that are distributed horizontally. This method successfully enhances the performance of attribute-aware semantic segmentation by reducing the ambiguity on segmenting the pedestrian’s orientation. Improvements on the pedestrian orientation segmentation are confidently shown by the proposed method in the experimental results, both in quantitative and qualitative views. This paper also discusses how the improved performance becomes an advantage in the autonomous driving system.

DOI： https://doi.org/10.1002/tee.23296

LFIR2Pose: Pose Estimation from an Extremely Low-Resolution FIR Image Sequence 査読有り

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

Proceedings of the 25th International Conference on Pattern Recognition 2021年1月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

OMEga-GAN: Object Manifold Embedding GAN for Image Generation by Disentangling Parameters into Pose and Shape Manifolds 査読有り

Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of the 25th International Conference on Pattern Recognition 頁： 7945 - 7952 2021年1月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Median-Shape Representation Learning for Category-Level Object Pose Estimation in Cluttered Environments 査読有り

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

Proceedings of the 25th International Conference on Pattern Recognition 頁： 4473 - 4480 2021年1月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

超低解像度FIR画像系列中での人物位置と行動の違いに着目した骨格推定法査読有り

岩田紗希, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 相澤知禎

精密工学会誌 87 巻 ( 1 ) 頁： 99 - 106 2021年1月

記述言語：日本語掲載種別：研究論文（学術雑誌）

Elderly monitoring systems are gaining attention in the modern aging society. For the purpose, Far-InfraRed (FIR) sensors are often used, because they can avoid privacy concerns and are robust to environmental lightings. The authors have previously proposed several methods for human skeleton estimation from an extremely low-resolution FIR image sequence whose resolution is 16 × 16 pixels. For more accurate estimation, this paper proposes a method that is robust to variations of human positions and actions in the FIR sequences. Specifically, to extract features robust to the human positions from the images by using a Convolutional Neural Network (CNN), a global max-pooling layer is inserted into the last layer instead of multiple pooling layers which are not suitable for low-resolution inputs. Also, a network with two branches is introduced that focuses on capturing spatial and temporal information respectively. Moreover, the network has a weighted sum mechanism of their outputs, which depends on the human actions. For evaluation, a dataset was created by capturing action sequences of a human at various positions in the FIR images. Through an experiment, we confirmed that the human motion can be smoothly estimated and that the estimation accuracy is improved by the proposed method.

Imageability Estimation using Visual and Language Features 査読有り

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

Proceedings of the 2020 International Conference on Multimedia Retrieval 頁： 306–310 2020年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

Modeling Eye-Gaze Behavior of Electric Wheelchair Drivers via Inverse Reinforcement Learning 査読有り

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

Proceedings of 2020 IEEE International Conference on Intelligent Transportation Systems 頁： 158 - 164 2020年9月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

Estimating the imageability of words by mining visual characteristics from crawled image data 査読有り

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

Multimedia Tools and Applications 79 巻 ( 25 ) 頁： 18167 - 18199 2020年7月

Performance Boost of Attribute-aware Semantic Segmentation via Data Augmentation for Driver Assistance 査読有り

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

頁： 293 - 298 2020年6月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

車両部位検出に基づく回帰を利用した車両台数の推定査読有り

新村文郷, 川西康友, 出口大輔, 井手一郎, 村瀬洋

知能と情報 32 巻 ( 3 ) 頁： 705 - 712 2020年6月

Simultaneous Image Matching for Person Re-identification via the Stable Marriage Algorithm 査読有り

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

IEEJ Transactions ON Electrical AND Electronic Engineering 15 巻 ( 6 ) 頁： 909 - 917 2020年4月

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

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2020 5 巻頁： 435 - 443 2020年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

LMS経由で手書きレポートを返却するWebサービス「かみレポ」の開発・評価査読有り

大平茂輝, 清谷竣也, 伊藤瑠哉, 岡本康佑, 谷川右京, 出口大輔, 戸田智基

情報処理学会論文誌：教育とコンピュータ（TCE） 6 巻 ( 1 ) 頁： 52 - 68 2020年2月

記述言語：日本語掲載種別：研究論文（学術雑誌）

高等教育における学習支援システム（LMS: Learning Management System）の重要性は年々高まっており，授業改善や学習分析などさまざまな目的のために活用されている．一方で，数式の記述や作図を必要とする授業や演習，試験など，紙媒体を主体的に扱う教育・学習環境は依然として多く残っており，それらの活動を支援するシステムが強く求められている．そこで本研究では，LMSと連携して手書きレポートを返却するWebサービスの実現を目指し，2016年度から「かみレポ」システムの開発を進めている．本稿では，半年間の試験運用時に実施した手書き数字の認識性能に関する評価と，運用開始後の1年6カ月間の運用評価をもとに，かみレポサービスの有効性と課題，今後の展望についてまとめる．

Occlusion-Aware Skeleton Trajectory Representation for Abnormal Behavior Detection 査読有り

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

2020年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

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

Lecture Note in Computer Science 11962 巻頁： 697 - 702 2020年1月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

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

Lecture Note in Computer Science 11962 巻頁： 214 - 225 2020年1月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

Attribute-Aware Loss Function for Accurate Semantic Segmentation Considering the Pedestrian Orientations 査読有り

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

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E103-A 巻 ( 1 ) 頁： 231 - 242 2020年1月

記述言語：英語掲載種別：研究論文（学術雑誌）

Numerous applications such as autonomous driving, satellite imagery sensing, and biomedical imaging use computer vision as an important tool for perception tasks. For Intelligent Transportation Systems (ITS), it is required to precisely recognize and locate scenes in sensor data. Semantic segmentation is one of computer vision methods intended to perform such tasks. However, the existing semantic segmentation tasks label each pixel with a single object’s class. Recognizing object attributes, e.g., pedestrian orientation, will be more informative and help for a better scene understanding. Thus, we propose a method to perform semantic segmentation with pedestrian attribute recognition simultaneously. We introduce an attribute-aware loss function that can be applied to an arbitrary base model. Furthermore, a re-annotation to the existing Cityscapes dataset enriches the ground-truth labels by annotating the attributes of pedestrian orientation. We implement the proposed method and compare the experimental results with others. The attribute-aware semantic segmentation shows the ability to outperform baseline methods both in the traditional object segmentation task and the expanded attribute detection task.

DOI： 10.1587/transfun.2019TSP0001

インテリジェントヘッドライトシステムにおける運転者による歩行者認知に効果的な点滅光照射パターンの分析査読有り

前田高志, 平山高嗣, 川西康友, 出口大輔, 井手一郎, 村瀬洋

精密工学会誌 85 巻 ( 12 ) 頁： 1157 - 1162 2019年12月

入力可変長PointNetによる自転車認識査読有り

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

精密工学会誌 85 巻 ( 12 ) 頁： 1117 - 1126 2019年12月

記述言語：日本語掲載種別：研究論文（学術雑誌）

近年，自動運転の実用化を目指して，距離センサであるLIDAR（Light Detection and
Ranging）を用いた周辺環境認識に関する研究が活発に行われている．これらの研究
の多くは自動車や歩行者の認識を目的としているが，一般道における自動運転を実用
化するためには，自転車の認識も重要である．自転車は歩行者に比べて移動速度が速
いため，衝突の危険性が高く，安全のために迅速かつ正確な認識が求められる．近年
，3D点群データを直接扱うDNN手法としてPointNetが提案されており，高い物体認識
精度が得られることが示されている．しかし，PointNetは入力点数が固定であるとい
う制約があり，認識対象物体の点数が大きく変化する場合にそのまま適用することは
難しい．そこで本論文では，LIDARにより計測された自転車の認識精度の向上を目的
とし，自転車の点群の分布形状を保持したダウンサンプリングとLIDARの測定精度を
考慮したアップサンプリングを行うサンプリングモジュールを提案する．ダウンサン
プリングでは，点群が低密度な部分の計測点が保存されるようサンプリングを行うこ
とで，自転車の点群の分布形状を保持したサンプリングを可能とする．アップサンプ
リングでは，LIDARの計測時に生じる誤差を考慮し，対象までの距離に応じて点群に
摂動を加えることで，点群の分布形状を大きく変化させることなく点群の密度の増加
を図る．この提案サンプリングモジュールの導入により，PointNetの入力の可変長化
を行う．KITTIデータセットを用いて評価実験を行い，提案手法によって認識精度が向
上することを確認した．

DOI： 10.2493/jjspe.85.1117

Scene-Adaptive Driving Area Prediction based on Automatic Label Acquisition from Driving Information 査読有り

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

Proceedings of the 5th IAPR Asian Conference on Pattern Recognition (ACPR2019) 2019年11月

Semantic Segmentation of Railway Images Considering Temporal Continuity 査読有り

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

Proceedings of the 5th IAPR Asian Conference on Pattern Recognition (ACPR2019) 2019年11月

An Analysis of How Driver Experience Affects Eye-Gaze Behavior for Robotic Wheelchair Operation 査読有り

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

Proceedings of 2019 IEEE International Conference on Computer Vision (ICCV) Workshops 頁： 4443 - 4451 2019年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

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

2019年9月

Similar Seasonal-Geo-Region Mining based on Visual Concepts in Social Media Photos 査読有り

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

Proceedings of the 5th IEEE Conference on Multimedia BigData 頁： 86 - 93 2019年9月

Estimation of the attractiveness of food photography based on image features 査読有り

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

IEICE Trans. on Information and Systems E102-D 巻 ( 8 ) 頁： 1590 - 1593 2019年8月

Hand Orientation Estimation in Probability Density Form

Kazuaki Kondo, Daisuke Deguchi, Atsushi Shimada

2019年6月

Estimating the Imageability of a sentence for image caption evaluation

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

2019年4月

Estimating the visual variety of concepts by referring to Web popularity 査読有り

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

Multimedia Tools and Applications 78 巻 ( 7 ) 頁： 9463 - 9488 2019年4月

記述言語：英語掲載種別：研究論文（学術雑誌）

Increasingly sophisticated methods for data processing demand knowledge on the semantic relationship between language and vision. New fields of research like Explainable AI demand to step away from black-boxed approaches and understanding how the underlying semantics of data sets and AI models work. Advancements in Psycholinguistics suggest, that there is a relationship from language perception to how language production and sentence creation work. In this paper, a method to measure the visual variety of concepts is proposed to quantify the semantic gap between vision and language. For this, an image corpus is recomposed using ImageNet and Web data. Web-based metrics for measuring the popularity of sub-concepts are used as a weighting to ensure that the image composition in a dataset is as natural as possible. Using clustering methods, a score describing the visual variety of each concept is determined. A crowd-sourced survey is conducted to create ground-truth values applicable for this research. The evaluations show that the recomposed image corpus largely improves the measured variety compared to previous datasets. The results are promising and give additional knowledge about the relationship of language and vision.

DOI： 10.1007/s11042-018-6528-x

他車両からの観測結果を事前知識とした車載カメラ映像中の人物再検出

川西康友, 出口大輔, 井手一郎, 村瀬洋

画像電子学会誌 48 巻 ( 2 ) 頁： 273 - 277 2019年4月

記述言語：日本語掲載種別：研究論文（学術雑誌）

本稿では，過去に別途検出されたことがある人物について，検出した時に得た知識を事前知識として利用することで，その人物を再び検出する際に精度よく検出する「人物再検出」という概念を提案する．また，この概念を車載カメラ映像中の人物検出に適用する方法を示す．本研究では自車がある地点で人物の検出をする際，自車より前にその人物の近くを通過した他車が，先にその場所の近くでその人物を検出している可能性が高いことに着目し，他車による観測を事前知識として人物再検出を行なう．実験により，独自に収集したデータセットを用いた評価において，事前知識を用いることで大きく検出性能が向上することを示す．

Summarization of multiple news videos considering the consistency of audio-visual contents 査読有り

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

International Journal of Semantic Computing 13 巻 ( 1 ) 頁： 135 - 155 2019年3月

Hard Negative Mining from in-Vehicle Camera Images based on Multiple Observations of Background Patterns 査読有り

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2019 5 巻頁： 435 - 442 2019年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2019 5 巻頁： 60 - 67 2019年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2019 5 巻頁： 313 - 320 2019年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Voting-based Hand-Waving Gesture Spotting from a Low-Resolution Far-Infrared Image Sequence 査読有り

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

Proceedings of 2018 IEEE International Conference on Visual Communications and Image Processing (VCIP2018) 2018年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

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

Proceedings of 20th IEEE Int. Symposium on Multimedia (ISM2018) 頁： 36 - 43 2018年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

赤外線センサアレイを用いた畳み込みRNNによる人物行動認識査読有り

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

精密工学会誌 84 巻 ( 12 ) 頁： 1025 - 1032 2018年12月

記述言語：日本語掲載種別：研究論文（学術雑誌）

This paper proposes a Deep Learning-based action recognition method from an extremely low-resolution FIR image sequence. The method recognizes daily actions by humans (e.g. walking, sitting down, standing up, and so on) 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 FIR image. To address these problems, this paper proposes a Deep Learning-based action recognition method whose inputs are the FIR images and their frame differences cropped by the gravity center of human regions.

低密度LIDAR点群からの歩行者検出査読有り

建部好輝, 出口大輔, 川西康友, 井手一郎, 村瀬洋

精密工学会誌 84 巻 ( 12 ) 頁： 1017 - 1024 2018年12月

記述言語：日本語掲載種別：研究論文（学術雑誌）

In recent years, the demand for pedestrian detection using LIDAR is increasing, as it can be used to prevent traffic accidents involving pedestrians. To avoid traffic accidents, detection of distant pedestrians is very important. However, they are scanned sparsely even if a dense-scan LIDAR is used, and this causes the degradation of the detection accuracy. There-fore, pedestrian detection from sparsely-scanned LIDAR point-clouds is expected to be developed. This paper proposes a LIDAR-based pedestrian detection method using 3DCNN. Since it is difficult to train a 3DCNN directly from sparse point-clouds, the proposed method converts them to a voxel representation using the kernel density estimation based on LIDAR characteristics. To evaluate the performance of the proposed method, an experiment using real-world LIDAR data was conducted. The results showed that the proposed method could detect pedestrians more accurately than detectors trained with other conventional features.

DOI： 10.2493/jjspe.84.1017

Localizing the Gaze Target of a Crowd of People 査読有り

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

2018年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Analyzing Headlight Flicker Patterns for Improving the Pedestrian Detectability from a Driver 査読有り

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

Proceedings of 2018 IEEE 21st International Conference on Intelligent Transportation Systems (ITSC2018) 頁： 3113 - 3118 2018年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Estimating the Scene-wise Reliability of LiDAR Pedestrian Detectors 査読有り

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

Proceedings of 2018 IEEE 21th International Conference on Intelligent Transportation Systems (ITSC2018) 頁： 3511 - 3516 2018年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Attribute-aware Semantic Segmentation of Road Scenes for Understanding Pedestrian Orientations 査読有り

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

Proceedings of 2018 IEEE 21th International Conference on Intelligent Transportation Systems (ITSC2018) 頁： 2698 - 2703 2018年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Estimation of Driver's Insight for Safe Passing based on Pedestrian Attributes 査読有り

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

Proceedings of 2018 IEEE 21th International Conference on Intelligent Transportation Systems (ITSC2018) 頁： 1041 - 1046 2018年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

テレビ会議話者間の視線一致知覚のための目領域合成手法査読有り

井上卓弥, 平山高嗣, 高橋友和, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 黒住隆行, 柏野邦夫

電気学会論文誌C 138 巻 ( 11 ) 頁： 1399 - 1409 2018年11月

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

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

2018年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

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

2018年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Camera DropoutとTrajectory Ensembleによる多カメラ間複数人物追跡査読有り

川西康友, 出口大輔, 井手一郎, 村瀬洋

電子情報通信学会論文誌 J101-D 巻 ( 8 ) 頁： 1079 - 1088 2018年8月

記述言語：日本語掲載種別：研究論文（学術雑誌）

複数カメラにわたる多人数追跡は，通常，対応付けの候補を減らすために複数のカメラの隣接関係をカメラネットワークというグラフ構造で表現し，カメラネットワーク上の隣接カメラ間での人物対応付けにより実現される．しかし，カメラ間の照明環境の違いや撮影した人物の向きの違いによって対応付けを誤ることがあり，このような場合に追跡が途切れることがある．この問題に対し，隣接カメラだけでなく，カメラネットワーク上で離れたカメラ間での人物対応付けをすることが考えられるが，必要以上に対応付け候補が増加してしまい，誤対応の原因となる．本論文では，本来のカメラネットワークからカメラを無作為に削除したカメラネットワークを複数作る（Camera Dropout）ことで，一部のカメラについては離れたカメラまで考慮した対応付けを行い，更に各カメラネットワーク上での追跡結果をアンサンブルクラスタリングの考え方で統合し，最終的な追跡結果を得るTrajectory Ensembleという手法を提案する．実験では，公開データセットから仮想的に生成した複数のデータセット上で評価を行い，既存の追跡手法に加えてTrajectory Ensembleを導入することにより，精度良く追跡ができることを確認した．

Visualization of Real World Activity on Group Work

Daisuke Deguchi, Kazuaki Kondo, Atsushi Shimada

Proceedings of 20th International Conference on HCI International 2018 (HCII2018) LNCS 10902 巻頁： 23 - 37 2018年7月

担当区分：筆頭著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

音象徴性を利用したオノマトペによる歩容の記述査読有り

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

人工知能学会論文誌 33 巻 ( 4 ) 頁： 1 - 9 2018年7月

Pedestrian Detectability Estimation Considering Visual Adaptation to Drastic Illumination Change 査読有り

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

IEICE Transactions on Information and Systems E101-D 巻 ( 5 ) 頁： 1457 - 1462 2018年5月

Development of 'KamiRepo' System with Automatic Student Identification to Handle Handwritten Assignments on LMS 査読有り

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

Proceedings of 2018 the IEEE Global Engineering Education Conference (EDUCON2018) 頁： 841 - 848 2018年4月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 Preliminary Study on Optimizing Person Re-identification using Stable Marriage Algorithm 査読有り

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

頁： 6 2018年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Efficient Pedestrian Scanning by Active Scan LIDAR 査読有り

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

Proceedings of International Workshop on Advanced Image Technology (IWAIT) 2018 頁： 1 - 4 2018年1月

Pedestrian Detection from Sparse Point-Cloud using 3DCNN 査読有り

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

Proceedings of International Workshop on Advanced Image Technology (IWAIT) 2018 頁： 1 - 4 2018年1月

Automatic selection of Web contents towards automatic authoring of a video biography 査読有り

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

Proceedings of 19th IEEE Int. Symposium on Multimedia (ISM2017) 頁： 304 - 307 2017年12月

Summarization of news videos considering the consistency of auditory and visual contents 査読有り

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

Proceedings of 19th IEEE Int. Symposium on Multimedia (ISM2017) 頁： 193 - 199 2017年12月

Toward Describing Human Gaits by Onomatopoeias 査読有り

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

Proceedings of 2017 IEEE International Conference on Computer Vision (ICCV2017) Workshops 頁： 1573 - 1580 2017年10月

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

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

Proceedings of Workshop on Human Factors in Intelligent Vehicles 頁： 32 - 36 2017年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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."

Detection of Similar Geo-Regions based on Visual Concepts in Social Photos 査読有り

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

2017年9月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Proposal of an encoded marker for working robots: An encoded marker easy to detect in various positions and under blur 査読有り

Norimasa Kobori, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Electronics and Communications in Japan 100 巻 ( 10 ) 頁： 59 - 69 2017年9月

Action Recognition from Extremely Low-Resolution Thermal Image Sequence 査読有り

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

Proceedings of the 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS2017) 2017年9月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

Estimation of the attractiveness of food photography focusing on main ingredients 査読有り

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

Proceedings of 9th Workshop on Cooking and Eating Activities (CEA2017) in conjunction with IJCAI2017 頁： 1 - 6 2017年8月

Regression of Feature Scale Tracklets for Decimeter Visual Localization 査読有り

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

Image and Vision Computing 68 巻頁： 53 - 63 2017年8月

記述言語：英語掲載種別：研究論文（学術雑誌）

Localization along a route is an everyday necessity for in-vehicle navigation systems, and a vital task for automated driving technologies. Visual ego-localization promises reliable accuracy even in challenging urban environments where Global Positioning Systems (GPSs) can fail. Using cameras for localization against a pre-constructed database requires either the creation of a dense three-dimensional feature point map and pose estimation of a query camera relative to this map, or image matching along a database route to determine the capture position of the query camera based on the most similar database image. While the latter method is potentially less computationally intensive and can provide a more compact database, localization accuracy is limited by the discrete positioning information at database frame capture locations. In this paper we propose an image matching method that makes use of image features which are pre-matched during database construction, allowing linear regression coefficients for the relationship between capture position and feature scale to be calculated. The capture position of matched query features can then be estimated to sub-database spacing resolution. By incorporating the visual localization system into a Bayes estimator, we demonstrate an average monocular vision localization accuracy of 0.33 m in tests on actual vehicle image streams.

DOI： 10.1016/j.imavis.2017.07.004

Headgear Recognition by Decomposing Human Images in the Thermal Infrared Spectrum 査読有り

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

Proceedings of the 15th International Conference on Quality in Research (QiR2017) 頁： 164 - 168 2017年7月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

頁： 1471 - 1477 2017年7月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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."

Monocular Localization within Sparse Voxel Maps 査読有り

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

Proceedings of the 2017 IEEE Intelligent Vehicles Symposium (IV2017) 頁： 493 - 498 2017年6月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Proposal of a spectral random dots marker using local feature for posture estimation 査読有り

Norimasa Kobori, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of IEEE Virtual Reality 2017 頁： 223 - 224 2017年3月

Deep Manifold Embedding for 3D Object Pose Estimation 査読有り

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2017 5 巻頁： 173 - 178 2017年3月

Human Wearable Attribute Recognition Using Probability-Map-Based Decomposition of Thermal Infrared Images 査読有り

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

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E100-A 巻 ( 3 ) 頁： 854 - 864 2017年3月

記述言語：英語掲載種別：研究論文（学術雑誌）

This paper addresses the attribute recognition problem, a
field of research that is dominated by studies in the visible spectrum. Only
a few works are available in the thermal spectrum, which is fundamentally
different from the visible one. This research performs recognition specif-
ically on wearable attributes, such as glasses and masks. Usually these
attributes are relatively small in size when compared with the human body,
on top of a large intra-class variation of the human body itself, therefore
recognizing them is not an easy task. Our method utilizes a decomposi-
tion framework based on Robust Principal Component Analysis (RPCA) to
extract the attribute information for recognition. However, because it is dif-
ficult to separate the body and the attributes without any prior knowledge,
noise is also extracted along with attributes, hampering the recognition
capability. We made use of prior knowledge; namely the location where
the attribute is likely to be present. The knowledge is referred to as the
Probability Map, incorporated as a weight in the decomposition by RPCA.
Using the Probability Map, we achieve an attribute-wise decomposition.
The results show a significant improvement with this approach compared
to the baseline, and the proposed method achieved the highest performance
in average with a 0:83 F-score.

Can We Detect Pedestrians using Low-resolution LIDAR? 査読有り

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2017 5 巻頁： 157 - 164 2017年2月

Wheelchair-user Detection Combined with Parts-based Tracking 査読有り

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2017 5 巻頁： 165 - 172 2017年2月

Can a Driver Assistance System Determine if a Driver is Perceiving a Pedestrian? 査読有り

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2017 4 巻頁： 611 - 616 2017年2月

Single Camera Vehicle Localization Using Feature Scale Tracklets 査読有り

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

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E100-A 巻 ( 2 ) 頁： 702 - 713 2017年2月

記述言語：英語掲載種別：研究論文（学術雑誌）

Advances in intelligent vehicle systems have led to modern automobiles being able to aid drivers with tasks such as lane following and automatic braking. Such automated driving tasks increasingly require reliable ego-localization. Although there is a large number of sensors that can be employed for this purpose, the use of a single camera still remains one of the most appealing, but also one of the most challenging. GPS localization in urban environments may not be reliable enough for automated driving systems, and various combinations of range sensors and inertial navigation systems are often too complex and expensive for a consumer setup. Therefore accurate localization with a single camera is a desirable goal.
In this paper we propose a method for vehicle localization using images captured from a single vehicle-mounted camera and a pre-constructed database.
Image feature points are extracted, but the calculation of camera poses is not required---instead we make use of the feature points' scale.
For image feature-based localization methods, matching of many features against candidate database images is time consuming, and database sizes can become large. Therefore, here we propose a method that constructs a database with pre-matched features of known good scale stability. This limits the number of unused and incorrectly matched features, and allows recording of the database scales into ``tracklets''. These ``Feature scale tracklets'' are used for fast image match voting based on scale comparison with corresponding query image features. This process reduces the number of image-to-image matching iterations that need to be performed while improving the localization stability. We also present an analysis of the system performance using a dataset with high accuracy ground truth. We demonstrate robust vehicle positioning even in challenging lane change and real traffic situations.

DOI： 10.1587/transfun.E100.A.702

視線遷移と瞬きの時系列パターンに基づく調理動作識別手法査読有り

井上裕哉, 平山高嗣, 道満恵介, 川西康友, 井手一郎, 出口大輔, 村瀬洋

電子情報通信学会論文誌 J100-A 巻 ( 1 ) 頁： 12 - 23 2017年1月

記述言語：日本語掲載種別：研究論文（学術雑誌）

本研究では，調理者の視線遷移と瞬きの時系列パターンに基づいて調理動作を識別する手法を提案する．視線情報が人間の行動を理解するうえで重要であることから，頭部に装着した視線計測装置により視線運動データを計測し，調理動作識別に用いる．視線パターンの表現には，視線情報に着目した動作認識において有用とされるN-gramを採用する．従来研究では，前フレームからの相対的な視線遷移のみがN-gramを構成する記号に用いられていた．これに対して本研究では，調理動作には調理対象への注視を持続させる振る舞いが頻繁に表れることから「停留」と，動作に対する集中を考慮するために「瞬き」を表現する記号を加えた．そして，高次元特徴を効率的に学習でき，特徴量のノイズに強いとされるRandom Forestを利用し，視線パターンが各調理動作クラスに属する事後確率を出力する識別器を構築した．実験結果から各調理動作の性質と識別に対する寄与度が高い視線パターンとの関係性を明らかにしたうえで，調理動作識別において従来手法よりも高い識別精度が得られ，提案手法の有効性を確認した．

Misclassification Tolerable Learning for Robust Pedestrian Orientation Classification 査読有り

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

頁： 481 - 486 2016年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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."

誤検出マイニングに基づくシーン適応型歩行者検出査読有り

鈴木悠暉, 出口大輔, 川西康友, 井手一郎, 村瀬洋

精密工学会誌 82 巻 ( 12 ) 頁： 1085 - 1091 2016年12月

記述言語：日本語掲載種別：研究論文（学術雑誌）

In recent years, demands for Advanced Driving Assistance Systems (ADAS) is increasing, and pedestrian detection has become one of the most important and popular technologies in this system. In the case of pedestrian detection using an in-vehicle camera, since the road environment varies widely according to difference in lightning, weather, etc., it is very difficult to handle them with a single classifier, and numerous false positives are detected. To overcome this problem, this paper proposes a novel pedestrian detection method by scene adaptation based on false positive mining. When we observe the appearance of false positives in in-vehicle camera images, those with similar features are found even in different road environments. The proposed method focuses on the appearance of the detected false positives, and considers it as a scene that the classifier is not good at. By analyzing such a false positive tendency in each scene, the proposed method associates the false positive tendency to each scene and then associates them to each training image. Then, classifiers are constructed so that they can cope with false positives observed in each scene. To evaluate the effectiveness of the proposed method, experiments were conducted on the Caltech Pedestrian Detection Benchmark datasets. Its results showed that the proposed method outperforms the method without adaptation.

DOI： 10.2493/jjspe.82.1085

Recognition of Texting-While-Walking by Joint Features based on Arm and Head Poses 査読有り

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

2016年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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."

Moving camera background-subtraction for obstacle detection on railway tracks 査読有り

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

Proceedings of 2016 IEEE International Conference on Image Processing (ICIP2016) 頁： 3967 - 3971 2016年9月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

Subjective Sensing of Real World Activity on Group Study 査読有り

Daisuke Deguchi, Kazuaki Kondo, Atsushi Shimada

Proceedings of the 18th International Conference on Collaboration Technologies (CollabTech2016) 頁： 5 - 8 2016年9月

担当区分：筆頭著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

作業用ロボットのための符号化マーカの提案査読有り

小堀訓成, 出口大輔, 井手一郎, 村瀬洋

電気学会論文誌C 136 巻 ( 9 ) 頁： 1367 - 1375 2016年9月

記述言語：日本語掲載種別：研究論文（学術雑誌）

It is becoming important for working robots to be able to identify and pick objects in various tasks. As in the recent Amazon Picking Challenge, using a marker for the picking task is a more practicable approach. However, a common marker code for working robots does not exist so far. Conventional marker codes as represented by QR code or ARToolKit marker cannot be reliably detected from various viewpoints. Thus in this paper, we propose a new encoded marker which is flexibile to the marker's positions and blur. The proposed marker can be detected by an approach based on the scale space theory independent from such conditions. In addition, the representation of data by M-sequence makes the encoded marker robust to blur. Experimental results showed the effectiveness of the proposed marker compared to the ARToolKit marker. Since the marker is more robust against ground clutter noise, various positions of markers and blur, it is more practicable.

DOI： 10.1541/ieejeiss.136.1367

Parts Selective DPM for detection of pedestrians possessing an umbrella 査読有り

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

Proceedings of 2016 IEEE Intelligent Vehicles Symposium (IV2016) 頁： 1053 - 1058 2016年6月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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."

Using Super-Pixels and Human Probability Map for Automatic Human Subject Segmentation 査読有り

Esmaeil Pourjam, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E99-A 巻 ( 5 ) 頁： 943 - 953 2016年5月

記述言語：英語掲載種別：研究論文（学術雑誌）

Human body segmentation has many applications in a wide
variety of image processing tasks, from intelligent vehicles to entertainment.
A substantial amount of research has been done in the field of segmentation
and it is still one of the active research areas, resulting in introduction of
many innovative methods in literature. Still, until today, a method that can
overcome the human segmentation problems and adapt itself to different
kinds of situations, has not been introduced. Many of methods today try to
use the graph-cut framework to solve the segmentation problem. Although
powerful, these methods rely on a distance penalty term (intensity difference
or RGB color distance). This term does not always lead to a good separation
between two regions. For example, if two regions are close in color, even
if they belong to two different objects, they will be grouped together, which
is not acceptable. Also, if one object has multiple parts with different
colors, e.g. humans wear various clothes with different colors and patterns,
each part will be segmented separately. Although this can be overcome
by multiple inputs from user, the inherent problem would not be solved.
In this paper, we have considered solving the problem by making use of a
human probability map, super-pixels and Grab-cut framework. Using this
map relives us from the need for matching the model to the actual body,
thus helps to improve the segmentation accuracy. As a result, not only the
accuracy has improved, it also became comparable to the state-of-the-art
interactive methods.

DOI： 10.1587/transfun.E99.A.943

A study on estimating the attractiveness of food photography 査読有り

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

Proceedings of 2016 IEEE Second International Conference on Multimedia Big Data 頁： 444 - 449 2016年4月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Reconstructing Face Image from the Thermal Infrared Spectrum to the Visible Spetrum 査読有り

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

Sensors, special issue on "Infrared and THz Sensing and Imaging" 16 巻 ( 4 ) 頁： 1 - 16 2016年4月

記述言語：英語掲載種別：研究論文（学術雑誌）

During the night or in poorly lit areas, thermal cameras are a better choice instead of normal cameras for security surveillance because they do not rely on illumination. A thermal camera is able to detect a person within its view, but identification from only thermal information is not an easy task. The purpose of this paper is to reconstruct the face image of a person from the thermal spectrum to the visible spectrum. After the reconstruction, further image processing can be employed, including identification/recognition. Concretely, we propose a two-step thermal-to-visible-spectrum reconstruction method based on Canonical Correlation Analysis (CCA). The reconstruction is done by utilizing the relationship between images in both thermal infrared and visible spectra obtained by CCA. The whole image is processed in the first step while the second step processes patches in an image. Results show that the proposed method gives satisfying results with the two-step approach and outperforms comparative methods in both quality and recognition evaluations.

DOI： 10.3390/s16040568

拡張Census Transformを用いた道路面の経時差分による車載カメラ映像からの不特定障害物検出査読有り

久徳遙矢, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋

電気学会論文誌C 136 巻 ( 4 ) 頁： 588 - 589 2016年4月

記述言語：日本語掲載種別：研究論文（学術雑誌）

This paper proposes a method for detecting general obstacles on a road by subtracting a present in-vehicle camera image sequence from its corresponding past image sequences using an illumination insensitive feature.
We conducted experiments using several image sequences captured under various illumination conditions, and confirmed the effectiveness of the proposed method.

DOI： 10.1541/ieejeiss.136.588

A classification method of cooking operations based on eye movement patterns 査読有り

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

Proceedings of Ninth Biennial ACM Symposium on Eye Tracking Research and Applications (ETRA2016) 頁： 205 - 208 2016年3月

HandWaving Gesture Detection Using a Far-Infrared Sensor Array with Thermo-Spatial Region of Interest 査読有り

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2016 頁： 545 - 551 2016年2月

Image transformation of eye areas for synthesizing eye-contacts in video conferencing 査読有り

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2016 3 巻頁： 273 - 279 2016年2月

Human Wearable Attribute Recognition using Decomposition of Thermal Infrared Images 査読有り

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

Proceedings of the 22th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2016) 頁： 123 - 127 2016年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

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

Proceedings of the 22th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2016) 頁： 28 - 33 2016年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

赤外線センサアレイを用いた人体追跡査読有り

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

電子情報通信学会論文誌 J99-D 巻 ( 1 ) 頁： 119 - 129 2016年1月

運転時の人間の視野特性を考慮した歩行者の見落としやすさ推定手法査読有り

谷繁龍之介, 道満恵介, 出口大輔, 目加田慶人, 井手一郎, 村瀬洋

電子情報通信学会論文誌 J99-D 巻 ( 1 ) 頁： 56 - 66 2016年1月

Position Interpolation using Feature Point Scale for Decimeter Visual Localization 査読有り

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

Proceedings of 2015 IEEE International Conference on Computer Vision (ICCV2015) Workshops 頁： 1 - 8 2015年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Detector Ensemble based on False Positive Mining for Pedestrian Detection 査読有り

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

Proceedings of the 3rd IAPR Asian Conference on Pattern Recognition (ACPR2015) 2015年11月

Generation of a video summary on a news topic based on SNS responses to news stories 査読有り

Kosuke Kato, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

Proc. 4th Int Workshop on Crowdsourcing for Multimedia (CrowdMM'15) in conjunction with ACMMM2015 頁： 21 - 26 2015年10月

他車による観測結果を用いた遠方人物検出査読有り

川西康友, 出口大輔, 井手一郎, 村瀬洋, 藤吉弘亘

Proceedings of 2015 IEEE Conference on Intelligent Transportation Systems (ITSC2015) 頁： 1215 - 1220 2015年9月

Tastes and textures estimation of foods based on the analysis of its ingredients list and image 査読有り

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

9281 巻頁： 326 - 333 2015年9月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

人物領域分割のための統計的形状フィードバック査読有り

Esmaeil Pourjam, 出口大輔, 井手一郎, 村瀬洋

電気学会論文誌C 135-C 巻 ( 8 ) 頁： 1000 - 1008 2015年8月

Typicality analysis of the combination of ingredients in a cooking recipe for assisting the arrangement of ingredients 査読有り

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

Proceedings of 2015 IEEE International Conference on Multimedia and Expo (ICME2012) 頁： 1 - 6 2015年7月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

（単板式RGB-TOFカメラを用いた歩行者の向き分類）査読有り

新村文郷, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 藤吉弘亘

Proceedings of Workshop on Environment Perception for Automated On-road Vehicles in conjunction with 2015 IEEE Intelligent Vehicles Symposium (IV2015) 頁： 7 - 11 2015年6月

Translating Apereo Software: A Case Study using Sakai and Transifex

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

2015年6月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

Multi-modal scene duplicate detection from news videos focusing on human faces 査読有り

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

International Journal of Semantic Computing 9 巻 ( 2 ) 頁： 215 - 237 2015年6月

記述言語：英語掲載種別：研究論文（学術雑誌）

In this paper, as a tool for structuring a large volume of archived news videos according to their semantic contents, we propose a method that effectively detects scene duplicates, assuming the presence of a person speaking in the videos. A scene duplicate is defined here as a pair of video segments taken at the same event from different viewpoints. When considering scenes where a subject is speaking in news videos, referring to the audio channel could be effective to detect scene duplicates regardless of viewpoints. However, it cannot be relied on when external audio sources overlap the original one or when the subject is actually not speaking. In contrast, the image channel can be useful in most cases. However, significant difference in viewpoints could prevent accurate detection. Therefore, we propose a method that combines the results obtained from both audio and image channels in order to improve the accuracy of scene duplicate detection from news videos. The proposed method was evaluated through an experiment with actual broadcast news videos by comparing it with a conventional method. As a result, we confirmed that the detection accuracy significantly improved by the proposed method in both recall and precision.

DOI： 10.1142/S1793351X15400048

教育用オープンソースソフトウェア群のローカライゼーションと共通翻訳メモリの開発査読有り

常盤祐司, 出口大輔, 宮崎誠, 平岡斉士, 喜多敏博, 梶田将司

情報処理学会デジタルプラクティス 6 巻 ( 2 ) 頁： 79 - 88 2015年4月

記述言語：日本語掲載種別：研究論文（学術雑誌）

大学教育で利用されているオープンソースソフトウェアの多くは英語圏で開発されているため日本語への翻訳が必要となる．今後大学では複数のシステムにより教育支援のためのIT環境を構築することが予想されるが，システム間で用語が異なっているとユーザに違和感を抱かせる．この課題に対して，大学教育で頻出する用語および用例を包含する大規模な共通翻訳メモリを作成することによって一貫性のある翻訳が実現できると考えた．また，翻訳メモリによる翻訳では実現できないコンテキスト依存の翻訳を可能とするgettext形式のPOファイルを併用することにより，Javaで実装されたSakaiとPHPで実装されたMoodleおよびMaharaをクラウドベースの翻訳支援システムであるTransifexを用いて同一のプロセスで翻訳した．本稿では大学教育用オープンソースソフトウェアに対して一貫性のある翻訳を目指して行ったプロジェクトについて述べる．

Adaptive Reference Image Selection for Temporal Object Removal from Frontal In-vehicle Camera Image Sequences 査読有り

Toru Kotsuka, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2015 頁： 233 - 239 2015年3月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

Estimation of Human Orientation using Coaxial RGB-Depth Images 査読有り

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2015 頁： 113 - 120 2015年3月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

Scene duplicate detection from news videos using image-audio matching focusing on human faces 査読有り

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

Proceedings of the 16th IEEE International Symposium on Multimedia (ISM2014) 頁： 71 - 77 2014年12月

Event detection based on twitter enthusiasm degree for generating a sports highlight video 査読有り

道満恵介, 富田大志, 井手一郎, 出口大輔, 村瀬洋

頁： 949 - 952 2014年11月

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

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

Proceedings of 2nd Workshop on User-Centred Computer Vision 2014年11月

Prediction of Driver's Pedestrian Detectability by Image Processing Adaptive to Visual Fields of View 査読有り

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

Proceedings of 2014 IEEE Conference on Intelligent Transportation Systems (ITSC2014) 頁： 1388 - 1393 2014年10月

Vision-based Vehicle Localization using a Visual Street Map with Embedded SURF Scale 査読有り

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

Proceedings of Computer Vision in Vehicle Technology with Special Session on Micro Aerial Vehicles (CVVT2014) 2014年9月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Spatial People Density Estimation from Multiple Viewpoints by Memory Based Regression 査読有り

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

Proceedings of the 22nd IAPR International Conference on Pattern Recognition (ICPR2014) 頁： 2209 - 2214 2014年8月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Single Camera Vehicle Localization Using SURF Scale and Dynamic Time Warping 査読有り

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

Proceedings of 2014 the IEEE Intelligent Vehicles Symposium (IV2014) 頁： 681 - 686 2014年6月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

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

Proceedings of 2014 IEEE Intelligent Vehicles Symposium (IV2014) 頁： 202 - 207 2014年6月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

カメラ間の位置関係に基づく画像間距離系列を用いた車載カメラ映像データベース検索による自車位置推定査読有り

久徳遙矢, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋

電気学会論文誌C 134 巻 ( 5 ) 頁： 702 - 710 2014年5月

記述言語：日本語掲載種別：研究論文（学術雑誌）

We propose an accurate ego-localization method by searching a streetview database composed of single front-view in-vehicle camera images. Previously, we proposed an image distance metric reflecting the positional relation of two cameras based on epipolar geometry analysis, and used it for ego-localization. However, since the method employed a dynamic time warping strategy to avoid the effect from outliers, both input and database images needed to be image sequences. To overcome this problem, the method proposed in this paper reformulates the previous image distance metric to a novel image distance that requires only a single in-vehicle camera image as an input, which is realized by considering the sequential property of the images in the database. We conducted experiments using multiple image sequences captured under various conditions by using an in-vehicle camera mounted on the windshield of a car. The experimental results showed that the proposed method could achieve an accuracy of 89%, and we confirmed its effectiveness.

DOI： 10.1541/ieejeiss.134.702

Estimation of the Representative Story Transition in a Chronological Semantic Structure of News Topics 査読有り

Kosuke Kato, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

Proceedings of the 4th International Conference on Multimedia Retrieval (ICMR2014) 頁： 487 - 491 2014年4月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

Can a Human be a Sensor? 査読有り

Atsushi Shimada, Daisuke Deguchi, Kazuaki Kondo, Takuya Funatomi

Proceedings of the 20th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2014) 頁： 242 - 245 2014年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2014 頁： 354 - 361 2014年1月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2014 頁： 115 - 121 2014年1月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

Scene dependent classifiers for pedestrian detection

Hidefumi Yoshida, Daichi Suzuo, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2013年11月

Automatic authoring of a domestic cooking video based on the description of cooking instructions 査読有り

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

Proceedings of 5th International Workshop on Multimedia for Cooking and Eating Activities (CEA'13) 頁： 21 - 26 2013年10月

Blur-invariant Traffic Sign Recognition Using Compact Local Phase Quantization 査読有り

Saleh Aly, Daisuke Deguchi, Hiroshi Murase

Proceedings of 2013 IEEE Conference on Intelligent Transportation Systems (ITSC2013) 頁： 821 - 827 2013年10月

Construction of a traffic sign detector based on voting type co-training 査読有り

Yuji Kojima, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of 2013 IEEE Conference on Intelligent Transportation Systems (ITSC2013) 頁： 1137 - 1142 2013年10月

Prediction of Pedestrian Detectability for Drivers by Image Processing and its Driver Adaptation 査読有り

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

Proceedings of the 6th Biennial Workshop on Digital Signal Processing for In-Vehicle Systems (DSP2013) 頁： 1 - 4 2013年9月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Pedestrian Detection by Scene Dependent Classifiers with Generative Learning 査読有り

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

Proceedings of 2013 IEEE Intelligent Vehicles Symposium (IV2013) 頁： 654 - 659 2013年6月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Segmentation of Human Instances Using Grab-cut and Active Shape Model Feedback 査読有り

Esmaeil Pourjam, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

Proceedings of IAPR Conference on Machine Vision Applications (MVA) 2013 頁： 77 - 80 2013年5月

異なる顔向きの顔認識査読有り

李析, 高橋友和, 出口大輔, 井手一郎, 村瀬洋

IEICE Transaction on Information and Systems, Special Section on Face Perception and Recognition E96-D 巻 ( 3 ) 頁： 531 - 537 2013年3月

低解像度QRコード認識のための2値グリッド拘束付き2段階超解像査読有り

加藤祐二, 高橋友和, 出口大輔, 井手一郎, 村瀬洋

電子情報通信学会論文誌 J96-D 巻 ( 2 ) 頁： 328 - 337 2013年2月

記述言語：日本語掲載種別：研究論文（学術雑誌）

QRコードは二次元コードの一種で，小面積に印刷するだけで様々な媒体に情報を付加することができ，製造における発注システムなどで利用されている．しかし，カメラとQRコードが離れるほどQRコード画像は相対的に低解像度となるため，認識が困難になる．そこで本論文では，低解像度のQRコード画像の認識性能の向上を目的として，QRコードの特徴を利用した複数フレーム超解像手法を提案する．本手法では，QRコードの認識が検出とデコードの2段階の処理からなることを利用して，それぞれの精度向上を行うために2段階の超解像処理を導入する．また，QRコードが2値のグリッド状のパターンで構成されることを利用し，これを超解像処理の拘束として用いる．更に，全てのQRコードが共通してもつパターンを利用して，ぼけを表す点拡がり関数(PSF：Point Spread Function)の推定を行う．実動画像を利用した認識実験の結果，撮影動画像そのままでは認識できないほど低解像度のQRコード画像に対して，提案手法は高い認識率を示した．このことから，提案手法の有効性を確認した．

Detection of Biased Broadcast Sports Video Highlights by Attribute-Based Tweets Analysis 査読有り

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

Lecture Note in Computer Science 7733 巻頁： 364 - 373 2013年1月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

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

Proceedings of International Workshop on Advanced Image Technology (IWAIT) 2013 頁： 231 - 235 2013年1月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Estimation of the human performance for pedestrian detectability based on visual search and motion features 査読有り

Masashi Wakayama, Daisuke Deguchi, Keisuke Doman, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

Proceedings of the 21st IAPR International Conference on Pattern Recognition (ICPR2012) 頁： 1940 - 1943 2012年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Virtual View Generation using Clustering based Local View Transition Model 査読有り

Xi Li, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of ACCV Workshop on Face Analysis: The Intersection of Computer Vision and Human Perception 2012年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

自車位置推定のための車載カメラ映像と市街地映像データベースの位置ずれや遮蔽に頑健なフレーム対応付け査読有り

久徳遙矢, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋

電子情報通信学会論文誌 J95-D 巻 ( 11 ) 頁： 1973 - 1982 2012年11月

記述言語：日本語掲載種別：研究論文（学術雑誌）

本論文では，自車前方を撮影した車載カメラ映像を用いた高精度な自車位置推定手法を提案する．提案手法では，車載カメラ映像と位置情報付き市街地映像データベースのフレーム対応付けを行い，対応づけられたデータベース中のフレームがもつ位置情報を参照することで自車位置推定を行う．同じ道路で撮られた映像同士であっても，走行速度や軌跡は異なるため，単純な画像照合による対応付けは困難である．そこで，画像特徴による照合ではなく，カメラ間の位置関係を反映したフレーム間の距離尺度を用いることで，フレーム対応付け精度の改善を図る．まず車載カメラ映像とデータベース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，基礎行列から算出されるエピポールの位置を用いてカメラ間の距離を算出する．そして，これを距離尺度とするDPマッチングにより，フレーム同士を対応づける．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．

Subtraction-Based Forward Obstacle Detection Using Illumination Insensitive Feature for Driving-Support 査読有り

Haruya Kyutoku, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

Proceedings of Computer Vision in Vehicle Technology: From Earth to Mars (CVVT2012) Part II 巻 ( LNCS 7584 ) 頁： 515 - 525 2012年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

Ryuhei Sato, Keisuke Doman, Daisuke Deguchi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

Proceedings of 2012 IEEE Conference on Intelligent Transportation Systems (ITSC2012) 頁： 1321 - 1326 2012年9月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

Detection and classification of repetitious human motions combining shift variant and invariant features 査読有り

Ichiro Ide, Taku Kuhara, Daisuke Deguchi, Tomokazu Takahashi, Hiroshi Murase

Proceedings of the 3rd International Conference on Emerging Security Technologies (EST2012) 頁： 86 - 89 2012年9月

Robust Face Super-Resolution Using Free-Form Deformations For Low-Quality Surveillance Video 査読有り

Tomonari Yoshida, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of 2012 IEEE International Conference on Multimedia and Expo (ICME2012) 頁： 368 - 373 2012年7月

放送ニュース映像からの発話ショットの抽出査読有り

熊谷章吾, 道満恵介, 高橋友和, 出口大輔, 井手一郎, 村瀬洋

International Journal of Semantic Computing 6 巻 ( 2 ) 頁： 179 - 204 2012年6月

磁気式位置センサを用いた気管支鏡ナビゲーションシステムのためのマーカが不要な実時間位置合わせ手法: 人体模型による評価査読有り

出口大輔, フォイヤーシュタインマルコ, 北坂孝幸, 末永康仁, 井手一郎, 村瀬洋, 今泉和良, 長谷川好規, 森健策

International Journal of Computer Assisted Radiology and Surgery 7 巻 ( 3 ) 頁： 359 - 369 2012年5月

Construction of a local attraction map according to social visual attention 査読有り

Ichiro Ide, Jiani Wang, Masafumi Noda, Tomokazu Takahashi, Daisuke Deguchi, Hiroshi Murase

Proceedings of the 5th International Conference on Intelligent Interactive Multimedia Systems and Services (IIMSS2012) 頁： 153 - 162 2012年5月

気管支鏡ナビゲーションシステムのためのハイブリッド位置追跡手法の開発と比較査読有り

羅雄彪, フォイヤーシュタインマルコ, 出口大輔, 北坂孝幸, 高畠博嗣, 森健策

Medical Image Analysis 16 巻 ( 3 ) 頁： 577 - 596 2012年4月

Integration of generative learning and multiple pose classifiers for pedestrian detection 査読有り

Hidefumi Yoshida, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Kunihiro Goto, Yoshikatsu Kimura, Takashi Naito

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2012 1 巻頁： 567 - 572 2012年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

遡及型追跡に基づく標識画像の自動収集を用いた標識検出器の高精度化査読有り

出口大輔, 道満恵介, 井手一郎, 村瀬洋

電子情報通信学会論文誌 J95-D 巻 ( 1 ) 頁： 76 - 84 2012年1月

担当区分：筆頭著者記述言語：日本語掲載種別：研究論文（学術雑誌）

本論文では，車載カメラ映像から多様な変化を含む標識画像を自動収集することにより，高精度な標識検出器を低コストで構築する手法を提案する．さまざまな環境で精度良く標識を検出するためには，多様な変化を含む標識画像を大量に収集し，それらを学習サンプルとして標識検出器を構築する必要がある．しかしながら，そのような標識の学習サンプルをさまざまな環境で網羅的に収集することは不可能である．また，遠く離れた標識の画像中のサイズは小さく，それらを自動もしくは半自動で大量に収集することは困難である．一方，ある時点では遠くの標識であったとしても，自車の走行に伴って遠くの標識も徐々に近づき，最終的には大きく撮影されるという特徴がある．このような大きく撮影された標識は自動検出可能であり，また，標識の時間方向への追跡も比較的容易である．そこで本論文では，まず近くで大きく撮影された標識を検出し，一時的に記憶しておいた過去の映像から遡及的に時間を遡りながら標識を追跡することによって，遠く離れた位置の低品質の標識を切り出して収集し，学習サンプルとして標識検出器を構築する手法を提案する．これにより，多様な変化を含む標識画像を自動で収集し，高精度な標識検出器をわずかな手作業で構築可能な手法を実現する．提案手法をさまざまな環境で撮影した車載カメラ映像に適用した結果，わずかな手作業でF値が約0.957の標識検出器が構築可能であることを確認した．

空撮画像と車載カメラ画像からの特徴点の時系列対応付けによる自車位置推定の高精度化査読有り

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

電子情報通信学会論文誌 J95-D 巻 ( 1 ) 頁： 111 - 121 2012年1月

記述言語：日本語掲載種別：研究論文（学術雑誌）

近年，高機能カーナビゲーションなどへの応用を目的とし，空撮画像と車載カメラ画像に共通して撮影されている道路面を対応づけることで高精度に自車位置を推定する手法が提案されている．従来は，道路面に印字されている路面標示の重心を特徴点として対応付けに用いていたが，このような特徴点は路面標示の欠損や遮へいに影響を受けやすいため，自車位置推定精度が十分ではなかった．そこで，本論文では，特徴点が十分に得られない場合においても，高精度，かつ頑健な自車位置推定手法を提案する．提案手法のアプローチは，（1）路面標示のコーナを特徴点とした空撮画像と車載カメラ画像の対応付け，（2）複数時刻の車載カメラ画像から得られる時系列の特徴点の対応付け，の二つである．実験の結果，前方車両が存在することにより路面標示が遮へいされるような実際の走行環境下において，提案手法による自車位置推定精度が従来手法に対して改善したことを確認した．

コントラスト特徴とアピアランス特徴の統合による道路標識の視認性推定査読有り

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

電子情報通信学会論文誌 J95-D 巻 ( 1 ) 頁： 122 - 130 2012年1月

記述言語：日本語掲載種別：研究論文（学術雑誌）

本論文では，背景とのコントラストおよび道路標識の見えに基づく画像特徴の統合利用による道路標識の視認性推定手法を提案する．
近年，様々な運転支援システムが自動車に搭載されるようになってきているが，過度の情報提供はドライバの注意散漫の原因となる．
そこで本研究では，道路交通において重要な情報源となる道路標識を対象とし，道路標識の視認性に応じてドライバへ情報を提供する不快感のない運転支援システムの実現を目指す．
提案手法では，道路標識の視認性に大きく影響する要因として，背景との明るさ，色，複雑さのコントラストに基づく画像特徴，および，道路標識自体の明るさ，色に基づく画像特徴を車載カメラ画像から抽出する．
そして，認知科学的な知見に基づいてこれらの画像特徴を統合し，道路標識の視認性を定量化する．
評価実験の結果，提案手法により高精度な視認性推定ができることを確認した．
また，提案手法で利用する複数の画像特徴およびそれらの統合モデルの有効性を確認した．

大規模放送映像アーカイブにおける出現パターンによる準同一映像区間の分類査読有り

社本裕司, 井手一郎, 出口大輔, 高橋友和, 村瀬洋

情報処理学会論文誌 52 巻 ( 12 ) 頁： 3593 - 3598 2011年12月

記述言語：日本語掲載種別：研究論文（学術雑誌）

我々は，日々増え続ける大量の放送映像からなるアーカイブを効果的かつ効率的に利用するために，映像内容に基づく構造化に取り組んでいる．本稿では，共通の枠組みの中で，様々な種類の放送映像を対象とした構造化を実現するための手段として，準同一（near-duplicate）映像の出現パターンに基づく分類を検討した結果を報告する．実際に，1,000 時間規模の放送映像に対する実験により，約360 万対の準同一映像区間を検出し，それを約4 万個のクラスタにまとめた後，6 種類の準同一映像クラスに分類した結果について分析することで，提案手法の効果と課題を明らかにする．

Web上の大量の写真に対する画像分類による観光マップの作成査読有り

王佳妮, 野田雅文, 高橋友和, 出口大輔, 井手一郎, 村瀬洋

情報処理学会論文誌 52 巻 ( 12 ) 頁： 3588 - 3592 2011年12月

記述言語：日本語掲載種別：研究論文（学術雑誌）

近年Web上には大量のジオタグ（撮影時のGPS情報）付き写真がアップロードされており，旅行を計画中のユーザは，旅行先の雰囲気を事前に視覚的に知ることができる．しかしながら，既存の写真共有サービスなどは単純に写真を地図上に配置するだけであるため，旅行先に関する土地勘がないユーザが必要とする情報を直感的に得ることは難しい．そこで，我々は大量の写真を風景によって分類し，多くの人が注
目した風景の写真を，旅行を計画するユーザに対して直感的に分かりやすく表現した地図である「観光マップ」を提案する．本稿では，観光マップ作成手法およびその有効性に関する初期的な検討結果について報告する．

Detection of Inconsistency between Subject and Speaker based on the Co-occurrence of Lip Motion and Voice Towards Speech Scene Extraction from News Videos 査読有り

Shogo Kumagai, Keisuke Doman, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of 2011 IEEE International Symposium on Multimedia (ISM2011) 頁： 311 - 318 2011年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

調理映像中の繰返し調理動作の検出査読有り

久原卓, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

電子情報通信学会論文誌 J94-D 巻 ( 12 ) 頁： 1983 - 1985 2011年12月

記述言語：日本語掲載種別：研究論文（学術雑誌）

本論文では，調理映像中の「切る」や「混ぜる」といった繰返し動作を検出する手法について検討した結果を報告する．繰返し動作の検出には，映像フレーム中の動作位置に依存しない特徴（CHLAC特徴）と依存する特徴（2値特徴）を用いる．これにより，繰返し動作領域の位置が大きく移動する動作及び一定である動作の両方に対応する．実際の料理番組映像に本手法を適用した結果，F値0.86の精度で検出できることを確認した．

複数画像系列の部分画像選択に基づく移動物体を含まない車載カメラ映像の生成査読有り

内山寛之, 高橋友和, 出口大輔, 井手一郎, 村瀬洋

電子情報通信学会論文誌 J94-D 巻 ( 12 ) 頁： 2093 - 2104 2011年12月

記述言語：日本語掲載種別：研究論文（学術雑誌）

近年，市街地映像を利用した運転支援システムが注目されている．また，“Googleストリートビュー”のような，市街地映像をインターネット上で閲覧できるサービスも提供されている．しかし，画像中に車両や歩行者などの移動物体が映り込むことが，遮へいやプライバシー保護の点で問題となっている．そこで本論文では，複数の車載全方位カメラ映像の部分画像を選択して貼り合わせることにより，移動物体を含まない映像を生成する手法を提案する．まず，カメラを搭載した車両が同じ経路を複数回走行することで，異なる時刻の複数の映像を収集する．そして，これらの映像間の時間方向と空間方向のレジストレーションを行う．次に，画像の同位置において移動物体が映っている頻度は少ないという仮定のもと，定義した評価関数を最小化することで，背景らしい部分画像を選択する．最後に，選択された部分画像を張り合わせることにより，移動物体を含まない市街地映像を作成する．市街地を撮影した実際の全方位カメラ映像を用いた実験により，移動物体の領域の96.5 %を除去した映像を生成することに成功した．

Scene Segmentation of Wedding Party Videos by Scenario-based Matching with Example Videos 査読有り

Kazuki Sawai, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of the 19th ACM International Multimedia Conference (ACM-MM2011) 頁： 1545 - 1548 2011年12月

MEMSジャイロセンサと単眼カメラを利用した高精度で頑健な姿勢推定査読有り

小堀訓成, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

計測自動制御学会論文集 47 巻 ( 10 ) 頁： 442 - 449 2011年10月

記述言語：日本語掲載種別：研究論文（学術雑誌）

In order to estimate accurate rotations of mobile robots and vehicle, we propose a hybrid system which combines a low-cost monocular camera with gyro sensors. Gyro sensors have 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 gyro sensors. To solve these problems we propose a method for combining these sensors based on Extended Kalman Filter. The errors of the gyro sensors are corrected by referring to the rotations obtained from the camera. In addition, by using the reliability judgment of camera rotations and devising the state value of the Extended Kalman Filter, even when the rotation is not continuously observable from the camera, the proposed method shows a good performance. Experimental results showed the effectiveness of the proposed method.

Low resolution QR-code recognition by applying super-resolution using the property of QR-codes 査読有り

Yuji Kato, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

Proceedings of the 11th International Conference on Document Analysis and Recognition (ICDAR2011) 頁： 992 - 996 2011年9月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

Power-efficient hardware architecture of K-Means clustering with Bayesian-Information-Criterion processor for multimedia processing applications 査読有り

Tse-Wei Chen, Chih-Hao Sun, Hsiao-Hang Su, Shao-Yi Chien, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEEE Journal on Emerging and Selected Topics in Circuits and Systems 1 巻 ( 3 ) 頁： 357 - 368 2011年9月

記述言語：英語掲載種別：研究論文（学術雑誌）

A power-efficient K-Means hardware architecture that can automatically estimate the number of clusters in the clustering process is proposed. The contributions of this work include two main aspects. The first is the integration of the hierarchical data sampling in the hardware to accelerate the clustering speed. The second is the development of the Bayesian-Information-Criterion (BIC) Processor" to estimate the number of clusters of K-Means. The architecture of the "BIC Processor" is designed based on the simplification of the BIC computations, and the precision of the logarithm function is also analyzed. The experiments show that the proposed architecture can be employed in different multimedia applications, such as motion segmentation and edge-adaptive noise reduction. Besides, the gate count of the hardware is 51 K with the 90-nm complimentary metal-oxide-semiconductor technology. It is also shown that this work can achieve high efficiency compared with a GPU, and the power consumption scales well with the number of clusters and the number of dimensions. The power consumption ranges between 10.72 and 12.95 mW in different modes when the operating frequency is 233 MHz."

DOI： 10.1109/JETCAS.2011.2165231

マルチメディア情報の補足による初心者向け料理レシピの作成へ向けて査読有り

志土地由香, 井手一郎, 中村裕一, 出口大輔, 高橋友和, 村瀬洋

電子情報通信学会論文誌 J94-A 巻 ( 7 ) 頁： 544 - 547 2011年7月

記述言語：日本語掲載種別：研究論文（学術雑誌）

既存のテキスト料理レシピから初心者に分かりにくい表現を検出した後，大量の料理レシピから抽出した情報に基づいてテキストを，調理動作の種類に応じて画像・映像を補足することで，分かりやすいマルチメディア料理レシピを作る方法を検討した．

On-road Obstacle Detection by Comparing Present and Past In-vehicle Camera Images 査読有り

Haruya Kyutoku, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

Proceedings of IAPR Conference on Machine Vision Applications (MVA) 2011 頁： 357 - 360 2011年6月

Estimation of Traffic Sign Visibility Considering Temporal Environmental Changes for Smart Driver Assistance 査読有り

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

Proceedings of 2011 IEEE Intelligent Vehicles Symposium (IV2011) 頁： 667 - 672 2011年6月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

Masafumi Noda, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Yoshiko Kojima, Takashi Naito

Proceedings of 2011 IEEE Intelligent Vehicles Symposium (IV2011) 頁： 460 - 465 2011年6月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

Hiroyuki Uchiyama, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

Proceedings of 2011 IEEE Intelligent Vehicles Symposium (IV2011) 頁： 290 - 295 2011年6月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

Daisuke Deguchi, Mitsunori Shirasuna, Keisuke Doman, Ichiro Ide, Hiroshi Murase

Proceedings of 2011 IEEE Intelligent Vehicles Symposium (IV2011) 頁： 72 - 77 2011年6月

担当区分：筆頭著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

位置依存型識別器を用いた車載カメラ画像からの路面標示検出査読有り

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

電気学会論文誌D 131 巻 ( 4 ) 頁： 466 - 474 2011年4月

記述言語：日本語掲載種別：研究論文（学術雑誌）

In this study, we propose a method for detecting road markings recorded in an image captured by an in-vehicle camera by using a position-dependent classifier. Road markings are symbols painted on the road surface that help in preventing traffic accidents and in ensuring traffic smooth. Therefore, driver support systems for detecting road markings, such as a system that provides warning in the case when traffic signs are overlooked, and supporting the stopping of a vehicle are required. It is difficult to detect road markings because their appearance changes with the actual traffic conditions, e. g. the shape and resolution change. The variation in these appearances depend on the positional relation between the vehicle and the road markings, and on the vehicle posture. Although these variations are quite large in an entire image, they are relatively small in a local area of the image. Therefore, we try to improve the detection performance by taking into account the local variations in these appearances. We propose a method in which a position-dependent classifier is used to detect road markings recorded in images captured by an in-vehicle camera. Further, to train the classifier efficiently, we propose a generative learning method that takes into consideration the positional relation between the vehicle and road markings, and also the vehicle posture. Experimental results showed that the detection performance when the proposed method was used was better than when a method involving a single classifier was used.

DOI： 10.1541/ieejias.131.466

Accurate and Robust Attitude Estimation of a Moving Vehicle Using MEMS Gyroscopes and a Monocular Camera 査読有り

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

Proceedings of 2010 Workshop on Picture Coding and Image Processing (WPCIP 2010) 2010年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

拡張DPマッチングを用いた視野角の異なるカメラ映像間の時空間対応付けによる自車位置推定査読有り

内山寛之, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

電子情報通信学会論文誌 J93-D 巻 ( 12 ) 頁： 2659 - 2665 2010年12月

記述言語：日本語掲載種別：研究論文（学術雑誌）

本論文では，データベース作成時に全方位カメラ，位置推定時に通常カメラを使用するアピアランスベースの自車位置推定手法を提案する．従来のアピアランスベースの自車位置推定では，データベース作成時と位置推定時で同一種類のカメラが使用されることが多い．しかし，位置推定精度やカメラの設置位置の制約などの点で問題となることがある．提案手法では，通常カメラ映像のフレームに対応する全方位カメラ映像のフレームと，そのフレーム中の領域を探索する．しかし，市街地では類似する物体が多く存在し，単一フレーム照合では正確な照合が難しい．そのため，複数フレーム照合を用いることで精度の向上を図る必要がある．これを実現するため，フレームと領域を考慮した映像間の照合コストを定式化する．そして，動的計画法によりこれを最小化するためのアルゴリズムを導入し，このアルゴリズムを用いて映像全体で最適に対応づける．データベース内のフレームには位置情報が付加されており，これにより自車位置を得る．実際に市街地で撮影した映像を用いた評価実験の結果，自車位置推定誤差が2m以下の割合が，領域の対応付けを行わない手法で77%，提案手
法で90%であり，提案手法の有効性を確認した．

Multimedia supplementation to a cooking recipe text for facilitating its understanding to inexperienced users 査読有り

Ichiro Ide, Yuka Shidochi, Yuichi Nakamura, Daisuke Deguchi, Tomokazu Takahashi, Hiroshi Murase

Proceedings of the 2nd Workshop on Cooking and Eating Activities (CEA2010) 頁： 242 - 247 2010年12月

Frontal Face Generation from Multiple Low-Resolution Non-Frontal Faces for Face Recognition 査読有り

Yuki Kono, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of the 10th International Workshop on Visual Surveillance 2010 2010年11月

Improvement of a traffic sign detector by retrospective gathering of training samples from in-vehicle camera image sequences 査読有り

Daisuke Deguchi, Keisuke Doman, Ichiro Ide, Hiroshi Murase

Proceedings of Computer Vision in Vehicle Technology: From Earth to Mars (CVVT2010) 2010年11月

Vehicle Ego-localization by Matching In-vehicle Camera Images to an Aerial Image 査読有り

Masafumi Noda, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Yoshiko Kojima, Takashi Naito

Proceedings of Computer Vision in Vehicle Technology: From Earth to Mars (CVVT2010) 2010年11月

Marker-Free Registration for Electromagnetic Navigation Bronchoscopy under Respiratory Motion

Marco Feuerstein, Takamasa Sugiura, Daisuke Deguchi, Tobias Reichl, Takayuki Kitasaka, Kensaku Mori

Proceedings of the 5th International Workshop on Medical Imaging and Augmented Reality (MIAR2010) LNCS 6326 巻頁： 237 - 246 2010年9月

色変動を考慮した生成型学習法による道路標識検出器の構築査読有り

道満恵介, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋

電子情報通信学会論文誌 J93-D 巻 ( 8 ) 頁： 1375 - 1385 2010年8月

記述言語：日本語掲載種別：研究論文（学術雑誌）

環境変化に対してロバストかつ高速な物体検出を可能とする識別器として，Violaらが提案したカスケード型識別器がある．これを用いて様々な環境下に存在する道路標識を高精度に検出するためには，多様な見えの変動を含んだ大量の標識画像を用いて識別器の学習を行う必要がある．しかしながら，多様な見えの変動をバランスよく含んだ大量の標識画像を手作業で収集するには多大なコストがかかる．そのため，本研究では生成型学習を用いてカスケード型識別器を構築することを考える．これまでにも生成型学習を用いて識別器を構築
する手法は提案されているが，形状やテクスチャの変動のみが考慮されており，色の変動は考慮されていない．
そこで本論文では，形状やテクスチャの変動に加えて色の変動も考慮し，より高い検出性能をもったカスケード型識別器を構築する手法を提案する．車載カメラ映像を用いた道路標識の検出実験の結果，本論文で提案する色の変動を考慮する生成型学習により，従来よりも高い検出性能をもつカスケード型識別器が構築できることを確認した．

Removal of Moving Objects from a Street-View Image by Fusing Multiple Image Sequences 査読有り

Hiroyuki Uchiyama, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

Proceedings of the 20th IAPR International Conference on Pattern Recognition (ICPR2010) 頁： 3456 - 3459 2010年8月

Classification of near-duplicate video segments based on their appearance patterns 査読有り

Ichiro Ide, Yuji Shamoto, Daisuke Deguchi, Tomokazu Takahashi, Hiroshi Murase

Proceedings of the 20th IAPR International Conference on Pattern Recognition (ICPR2010) 頁： 3129 - 3133 2010年8月

Estimation of Traffic Sign Visibility Toward Smart Driver Assistance 査読有り

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

Proceedings of 2010 IEEE Intelligent Vehicles Symposium (IV2010) 頁： 45 - 50 2010年6月

Construction of cascaded traffic sign detector using generative learning 査読有り

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

Proceedings of the 4th International Conference on Innovative Computing, Information and Control (ICICIC2009) 2009年12月

Labeling News Topic Threads with Wikipedia Entries 査読有り

Tomoki Okuoka, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of the 1st International Workshop on Content-Based Audio/Video Analysis for Novel TV Services (CBTV2009) 頁： 501 - 504 2009年12月

Automated Anatomical Labeling of Bronchial Branches Extracted from CT Datasets Based on Machine Learning and Combination Optimization and Its Application to Bronchoscope Guidance 査読有り

Kensaku Mori, Shunsuke Ota, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Shingo Iwano, Yoshinori Hasegawa, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2009) LNCS 5762, Part II 巻頁： 707 - 714 2009年9月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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

Low-resolution Character Recognition by Video-based Super-resolution 査読有り

大倉直, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

Proceedings of the 10th International Conference on Document Analysis and Recognition (ICDAR2009) 頁： 191 - 195 2009年7月

画像位置合わせに基づく気管支鏡追跡のための選択的な画像間類似度計算手法査読有り

出口大輔, 森健策, フォイヤーシュタインマルコ, 北坂孝幸, Calvin R. Maurer Jr., 末永康仁, 高畠博嗣, 森雅樹, 名取博

Medical Image Analysis 13 巻 ( 4 ) 頁： 621 - 633 2009年6月

An improved method for automated recognition of bronchial tree structure by optimizing combinations of candidate anatomical names 査読有り

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 4 巻頁： 327 - 328 2009年6月

Ego-localization using Streetscape Image Sequences from In-vehicle Cameras 査読有り

Hiroyuki Uchiyama, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

Proceedings of 2009 IEEE Intelligent Vehicles Symposium (IV2009) 頁： 185 - 190 2009年6月

Automatic Calibration of an In-vehicle Gaze Tracking System Using Driver's Typical Gaze Behavior 査読有り

Kenji Yamashiro, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase, Kazunori Higuchi, Takashi Naito

Proceedings of 2009 IEEE Intelligent Vehicles Symposium (IV2009) 頁： 998 - 1003 2009年6月

Recognition of Road Markings from In-Vehicle Camera Images by a Generative Learning Method 査読有り

Masafumi Noda, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Yoshiko Kojima, Takashi Naito

Proceedings of IAPR Conference on Machine Vision Applications (MVA) 2009 頁： 514 - 517 2009年5月

A method for accelerating bronchoscope tracking based on image registration by using GPU 査読有り

Takamasa Sugiura, Daisuke Deguchi, Marco Feuerstein, Takayuki Kitasaka, Yasuhito Suenaga, Kensaku Mori

Proceedings of SPIE Medical Imaging 2009 7261 巻頁： 726108 - 1 2009年2月

Automatic mediastinal lymph node detection in chest CT 査読有り

Marco Feuerstein, Daisuke Deguchi, Takayuki Kitasaka, Shingo Iwano, Kazuyoshi Imaizumi, Yoshinori Hasegawa, Yasuhito Suenaga, Kensaku Mori

Proceedings of SPIE Medical Imaging 2009 7260 巻頁： 1 - 11 2009年2月

計算機支援医用画像診断のための共通基盤システムの開発査読有り

二村幸孝, 出口大輔, 北坂孝幸, 末永康仁, 森健策

Medical Imaging Technology 26 巻 ( 5 ) 頁： 327 - 337 2008年11月

記述言語：日本語掲載種別：研究論文（学術雑誌）

本稿では，臓器・疾病横断型の診断支援を実現するための共通基盤システムについて述べる．医用画像に含まれる多量の情報を最大限に活用することが可能な臓器・疾病横断型の診断支援は，医師の負担軽減，診断の質的向上を実現する上で，今後，必要不可欠なると考えられる．我々は，この次世代の診断支援を実現するために共通基盤システムを開発している．この共通基盤システムは，診断支援機能を統合化するための仕組みを備えており，臓器・疾病横断型の診断支援や医師の診断ワークフローに沿う診断支援を実現することができる．本稿では，この共通基盤システムおよびその構成技術について詳述し，既存の医用画像処理ソフトウェアと比較実験を行い，本共通基盤システムが，多臓器・多疾病を対象とする計算機支援医用画像診断システムを実現するための優れた拡張性を有していることを

PLUTO: A Common CAD Platform for Multiorgan Multidisease CAD (MoMd-CAD) 査読有り

Yukitaka Nimura, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga

RSNA (Radiological Society of North America) Scientific Assembly and Annual Meeting Program 2008 頁： 904 2008年11月

A Method for Accelerating Bronchoscope Tracking Based on Image Registration by GPGPU 査読有り

Takamasa Sugiura, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga

Proceedings of International Workshop on Augmented environments for Medical Imaging and Computer-aided Surgery (AMI-ARCS) 2008 頁： 130 - 139 2008年9月

Improvement of Accuracy of Marker-Free Bronchoscope Tracking Using Electromagnetic Tracker Based on Bronchial Branch Information 査読有り

Kensaku Mori, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi, Hirotsugu Takabatake

Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2008) LNCS 5242, Part II 巻頁： 535 - 542 2008年9月

Augmented display of anatomical names of bronchial branches for bronchoscopy assistance 査読有り

Shunsuke Ota, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings of the 4th International Workshop on Medical Imaging and Augmented Reality (MIAR2008) LNCS 5128 巻頁： 377 - 384 2008年8月

An improved method for bronchoscope tracking using an electromagnetic tracker without fiducial markers 査読有り

Daisuke Deguchi, Kazuyoshi Ishitani, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi

Proceedings of the 22st International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2008) 3 巻頁： S301 2008年6月

Automated anatomical labeling of bronchaial branches using multiple classifiers and its application to bronchoscopy guidance 査読有り

Shunsuke Ota, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings of the 22st International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2008) 3 巻頁： S269 2008年6月

Fiducial-free bronchoscope tracking using ultra-tiny electromagnetic tracker based on non-rigid transformation technique 査読有り

Kensaku Mori, Kazuyoshi Ishitani, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi

Proceedings of the 22st International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2008) 3 巻頁： S105 2008年6月

Automated anatomical labeling of bronchial branches using multiple classifiers and its application to bronchoscopy guidance based on fusion of virtual and real bronchoscopy 査読有り

Shunsuke Ota, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings of SPIE Medical Imaging 2008 6916 巻頁： 1 - 12 2008年2月

Bronchoscope Tracking Without Fiducial Markers Using Ultra-tiny Electromagnetic Tracking System and Its Evaluation in Different Environments 査読有り

Kensaku Mori, Daisuke Deguchi, Kazuyoshi Ishitani, Takayuki Kitasaka, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi, Hirotsugu Takabatake

Proceedings of the 10th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2007) LNCS 4792, Part II 巻頁： 644 - 651 2007年10月

A method for bronchoscope tracking using position sensor without fiducial markers 査読有り

Daisuke Deguchi, Kazuyoshi Ishitani, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Yoshinori Hasegawa, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings of the 21st International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2007) 2 巻頁： S11-S13 2007年6月

A method for bronchoscope tracking using position sensor without fiducial markers 査読有り

Daisuke Deguchi, Kazuyoshi Ishitani, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings of SPIE Medical Imaging 2007 6511 巻頁： 1 - 0 2007年2月

Easy and stable bronchoscope camera calibration technique for bronchoscope navigation system 査読有り

Kazuyoshi Ishitani, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings of SPIE Medical Imaging 2007 6509 巻頁： 1 - 1 2007年2月

Compensation of Electromagnetic trackintg system using an optical tracker and its application to bronchoscopy navigation system 査読有り

Kensaku Mori, Kazuyoshi Ishitani, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings of SPIE Medical Imaging 2007 6509 巻頁： 1 - 0 2007年2月

3次元前立腺モデルに対する仮想針生検システムを用いた前立腺がん検出のための針生検手法の評価査読有り

野口正典, 出口大輔, 鳥脇純一郎, 森健策, 目加田慶人, 松岡啓

International Journal of Urology 13 巻 ( 10 ) 頁： 1296 - 1303 2006年10月

A preliminary study on introduction of a magnetic tracking sensor for bronchoscope navigation system 査読有り

Kazuyoshi Ishitani, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings of International Workshop on Augmented environments for Medical Imaging and Computer-aided Surgery (AMI-ARCS) 2006 2006年10月

Bronchoscope Tracking Based on Image Registration Using Multiple Initial Starting Points Estimated by Motion Prediction 査読有り

Kensaku Mori, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Calvin R. Maurer Jr.

Proceedings of the 9th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2006) LNCS 4191, Part II 巻頁： 645 - 652 2006年10月

Detection of liver cancer regions from dynamic CT images 査読有り

Yuichiro Hayashi, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yoshito Mekada, Yasuhito Suenaga

Proceedings of the 20th International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2006) 1 巻頁： 524 - 525 2006年6月

Image-based bronchoscope tracking using motion predication and multiple searches 査読有り

Kensaku Mori, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings of the 20th International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2006) 1 巻頁： 178 - 181 2006年6月

位置センサと画像位置合わせの統合による気管支鏡追跡手法査読有り

出口大輔, 秋山健太, 森健策, 北坂孝幸, 末永康仁, Calvin R. Maurer Jr., 高畠博嗣, 森雅樹, 名取博

Computer Aided Surgery 11 巻 ( 3 ) 頁： 109 - 117 2006年5月

Branch identification method for CT-guided bronchoscopy based on eigenspace image matching between real and virtual bronchoscopic images 査読有り

Riyoko Shinohara, Kensaku Mori, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings of SPIE Medical Imaging 2006 6143 巻頁： 14 - 1 2006年2月

多時相CT像からのCT値の確率分布推定に基づく肝臓領域抽出査読有り

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

コンピュータ支援画像診断学会論文誌 9 巻 ( 4 ) 頁： 36 - 48 2006年1月

担当区分：筆頭著者記述言語：日本語掲載種別：研究論文（学術雑誌）

本論文では，造影3次元腹部X線CT像からCT値の確率分布を解析することにより，肝臓領域を自動抽出する手法について述べる．肝臓のCT値分布は隣接する脾臓や筋肉のCT値分布と非常に類似しているため，単一時相からしきい値処理を用いて肝臓領域を抽出することは困難である．本論文では，早期相と晩期相の2次元ヒストグラムから肝臓，脾臓，筋肉に対応するCT値分布を推定し，肝臓領域抽出に用いるしきい値を自動的に決定する．具体的には，各臓器のCT値分布を正規分布と仮定し，EMアルゴリズムを用いてそれぞれの分布を推定する．推定された分布を用いて，肝臓領域，肝細胞がん領域を抽出することで，肝細胞がんを含む肝臓領域を抽出する．また，肝臓外領域を抽出することで肝臓に隣接する筋肉等への過抽出を抑制し，最後に輪郭を補正し肝臓領域を得る．本手法を早期相，晩期相の3次元腹部X線CT像26例に適用した結果，24例で良好に肝臓領域を抽出することが可能であった．

Development of a Virtual Needle Biopsy Simulation System for the Virtual Prostate 査読有り

Daisuke Deguchi, Kensaku Mori, Yoshito Mekada, Jun-ichi Hasegawa, Junichiro Toriwaki, Masanori Noguchi

Systems and Computers in Japan 37 巻 ( 1 ) 頁： 93 - 104 2006年1月

担当区分：筆頭著者記述言語：英語掲載種別：研究論文（学術雑誌）

This paper discusses the virtual prostate needle biopsy system and the construction of the virtual prostate model, considering the actual distribution of prostate abnormalities. A needle biopsy simulation is performed for the constructed virtual prostate, and the actual biopsy procedure in the clinical situation is evaluated. The prostate needle biopsy is a histologic diagnosis procedure in which a sample is acquired from the prostate tissue by needle biopsy and is inspected under a microscope. In order to achieve reliable prostate needle biopsy, it is necessary to consider systematically and numerically the number of needles required, and their locations and insertion angles.
For such a purpose, a system is developed in which a virtual prostate is constructed on a computer and the biopsy procedure is evaluated quantitatively by performing virtually the prostate needle biopsy. Furthermore, two different models are constructed, for the prostate with and without hypertrophy, based on the actual statistical distribution data for
prostate abnormalities. Each model is partitioned into the peripheral zone and the transition zone. The constructed
virtual prostate is input into the virtual needle biopsy simulation system, and three different systematic biopsy procedures actually used at clinical sites, and four different needle biopsy procedures, are experimentally evaluated.
The experiments show that the insertion angle that maximizes the hit probability is not always the same as the
insertion angle that maximizes cancer sample acquisition. It is evident that the proposed method can indicate a biopsy
procedure which realizes a high hit probability with a small number of needles.

DOI： 10.1002/scj.20181

Hybrid Bronchoscope Tracking Using a Magnetic Tracking Sensor and Image Registration 査読有り

Kensaku Mori, Daisuke Deguchi, Kenta Akiyama, Takayuki Kitasaka, Calvin R. Maurer Jr., Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings of the 8th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2005) LNCS 3750, Part II 巻頁： 543 - 550 2005年10月

A method for bronchoscope tracking by combining a position sensor and image registration 査読有り

Daisuke Deguchi, Kenta Akiyama, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga, Jun-ichi Hasegawa, Junichiro Toriwaki, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings of the 19th International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2005) 1281 巻頁： 630 - 635 2005年6月

造影3次元腹部X線CT像からの肝臓領域自動抽出手法の開発査読有り

林雄一郎, 出口大輔, 森健策, 目加田慶人, 末永康仁, 鳥脇純一郎

コンピュータ支援画像診断学会論文誌 8 巻 ( 1_3 ) 頁： 18 - 30 2004年11月

記述言語：日本語掲載種別：研究論文（学術雑誌）

本稿では，造影3次元腹部X線CT像から肝臓領域を自動抽出する手法について述べる．肝臓の診断では複数の時相のCT画像を用いるため，肝臓を対象としたコンピュータ支援診断システムにおいては，複数の時相から肝臓領域を抽出することは非常に重要である．本稿では特に肝細胞がんの診断に重要とされる早期相，晩期相からの肝臓領域抽出を行う．まず，晩期相においてCT値ヒストグラムを解析し，肝臓に対応するCT値の範囲を自動決定し，しきい値処理によりおおまかな肝臓領域を抽出する．次に，ユークリッド距離に基づく図形分割・統合処理により肝臓に接している他臓器を除去し，最後に輪郭を補正し肝臓領域を得る．早期相に対しては，晩期相から抽出した肝臓領域を早期相のCT像にマッピングし，輪郭領域を修正することで肝臓領域を得る．本手法を早期相，晩期相の3次元腹部X線CT像19症例に適用した結果，ほぼ良好に肝臓領域を抽出することが可能であった．

Fast and Accurate Bronchoscope Tracking using Image Registration and Motion Prediction 査読有り

Jiro Nagao, Kensaku Mori, Tsutomu Enjoji, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Jun-ichi Hasegawa, Junichiro Toriwaki, Hirotsugu Takabatake, Hiroshi Natori

Proceedings of the 7th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2004) LNCS 3217, Part II 巻頁： 551 - 558 2004年9月

Improved camera-tracking method by combining motion prediction and image registration for bronchoscope navigation system 査読有り

Kensaku Mori, Tsutomu Enjoji, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Junichiro Toriwaki, Hiroshi Natori, Hirotsugu Takabatake

Proceedings of the 18th International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2004) 1268 巻頁： 1261 2004年6月

New image similarity measures for bronchoscope tracking based on image registration between virtual and real bronchoscopic images 査読有り

Kensaku Mori, Tsutomu Enjoji, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Junichiro Toriwaki, Hirotsugu Takabatake, Hiroshi Natori

Proceedings of SPIE Medical Imaging 2004 5639 巻頁： 165 - 176 2004年2月

仮想前立腺に対する針生検シミュレーションシステムの開発査読有り

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

電子情報通信学会論文誌 J87-D-II 巻 ( 1 ) 頁： 281 - 289 2004年1月

担当区分：筆頭著者記述言語：日本語掲載種別：研究論文（学術雑誌）

本論文では,前立腺針生検シミュレーションシステムと実際の前立腺病変分布を考慮した仮想前立腺モデルの作成について述べる.また,作成した仮想前立腺に対する針生検シミュレーションを行い,実際の臨床で用いられている生検手法の評価を行う.前立腺針生検とは,前立腺内の組織を生検針により採取し,顕微鏡で検査する組織診断方法である.確実な前立腺針生検を行うには,針の本数,配置法,挿入角度等を組織的かつ数値的に検討する必要がある.そこで,計算機上に仮想的な前立腺を作成し,仮想的な前立腺針生検を行うことで生検手法を定量的に評価するシステムを開発した.また,実際の前立腺における病変分布の統計的なデータをもとに,肥大症の前立腺とそうでない前立腺の2種類のモデルを作成し,それぞれのモデルに対し辺縁領域(peripheral zone),移行領域(transition zone)への分類を行った.作成した仮想前立腺を仮想針生検シミュレーションシステムに入力し,臨床で用いられている系統的分割生検3種類と別の4種類の生検手法に対する評価実験を行った.実験の結果,ヒット確率を最大にする穿刺角度とがんの採取量を最大にする穿刺角度は必ずしも一致せず,少ない針の本数で高いヒット確率を得る生検手法の存在を,本システムを用いて採すことが可能であることを確認した.

New Image Similarity Measure for Bronchoscope Tracking Based on Image Registration 査読有り

Daisuke Deguchi, Kensaku Mori, Yasuhito Suenaga, Jun-ichi Hasegawa, Junichiro Toriwaki, Hirotsugu Takabatake, Hiroshi Natori

Proceedings of the 6th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2003) LNCS 2878 巻頁： 399 - 406 2003年11月

New calculation method of image similarity for endoscope tracking based on image registration in endoscope navigation 査読有り

Daisuke Deguchi, Kensaku Mori, Yasuhito Suenaga, Jun-ichi Hasegawa, Junichiro Toriwaki, Hiroshi Natori, Hirotsugu Takabatake

Proceedings of the 17th International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS2003) 1256 巻頁： 460 - 466 2003年6月

実気管支鏡と仮想化気管支鏡の画像間位置合わせとエピポーラ幾何解析に基づく気管支鏡カメラの追跡査読有り

森健策, 出口大輔, 杉山淳, 末永康仁, 鳥脇純一郎, Calvin R. Maurer Jr., 高畠博嗣, 名取博

Medical Image Analysis 6 巻頁： 321 - 336 2002年9月

Camera motion tracking of real bronchoscope using epipolar geometry analysis and CT derived bronchoscopic images 査読有り

Daisuke Deguchi, Kensaku Mori, Jun-ichi Hasegawa, Junichiro Toriwaki, Hirotsugu Takabatake, Hiroshi Natori

Proceedings of SPIE Medical Imaging 2002 4683 巻頁： 30 - 41 2002年2月

A method for tracking the camera motion of real endoscope by epipolar geometry analysis and virtual endoscopy system 査読有り

Kensaku Mori, Daisuke Deguchi, Jun-ichi Hasegawa, Yasuhito Suenaga, Junichiro Toriwaki, Hirotsugu Takabatake, Hiroshi Natori

Proceedings of the 4th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2001 LNCS 2208 巻頁： 1 - 8 2001年10月

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