Faculty Profiles - Deguchi Daisuke

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Pedestrian Intensive Scanning for Active-scan LIDAR International conference

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

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

Event date： 2019

Language：English Presentation type：Poster presentation

Venue：Vienna House Diplomat Prague, Prague, Czech Republic

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

電動車いす運転の熟達に伴う視行動変化の分析

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

画像の認識・理解シンポジウム(MIRU) 2019.8.1

Event date： 2019

Language：Japanese Presentation type：Poster presentation

Venue：グランキューブ大阪（大阪府立国際会議場）

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

Class Augmentation For Semantic Segmentation by Integrating Multiple Methods

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

2019.12.12

環境認識に関する基礎と最近の動向

出口大輔

日本機械学会東海支部講習会 2019.12.5

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

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

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

Semantic Segmentation of Railway Images Considering Temporal Continuity International conference

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

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

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

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

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

Event date： 2019

Language：English Presentation type：Poster presentation

Venue：COEX Convention Center, Seoul, Korea

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

DOI： 10.1109/ICCVW.2019.00545

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

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

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

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

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

5th IEEE Conference on Multimedia BigData 2019.9.11

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

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

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

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

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

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

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

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

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

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

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

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

Event date： 2019

Language：English Presentation type：Oral presentation (general)

Venue：大同大学

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

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

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

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

CityWalks: An Extended Dataset for Attribute-aware Semantic Segmentation

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

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

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

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

IEICE Technical Report (MVE) 2019.8.29

3つの学習特徴に基づく料理レシピの地域属性推定

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

電子情報通信学会魅力工学研究会シンポジウム2019 2019.8.28

見えに基づく同一料理カテゴリの料理に関する典型度分析

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

電子情報通信学会魅力工学研究会シンポジウム2019 2019.8.28

欠損復元AutoEncoderによる遮蔽に頑健な物体姿勢推定の検討

立道大樹, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 安間絢子

画像の認識・理解シンポジウム(MIRU) 2019.8.1

Event date： 2019

Language：Japanese Presentation type：Poster presentation

Venue：グランキューブ大阪（大阪府立国際会議場）

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

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

Kazuaki Kondo, Atsushi Shimada, Daisuke Deguchi

HCG Symposium 2018 2018.12.13

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