Faculty Profiles - Deguchi Daisuke

Presentations -

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Pedestrian Recognition for Proa ctive Driving Support System

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

2016.10.19

Ja Sakai Panel Session

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

Open Apereo 2016 2016.5.25

Event date： 2016

Language：English Presentation type：Oral presentation (general)

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

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

Obstacle detection with train frontal view camera

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

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

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

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

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

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

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

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

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

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

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

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

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

2016 IEEE Intelligent Vehicles Symposium (IV2016) 2016.6.19

Event date： 2016

Language：English Presentation type：Poster presentation

Venue：Gothenburg, Sweden

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

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

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

IEICE Technical Report (PRMU) 2016.6.14

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

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

IEICE Technical Report (PRMU) 2016.6.14

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

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

IEICE Technical Report (PRMU) 2016.6.13

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

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

IEICE Technical Report (MVE) 2016.6.2

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

川西康友, 出口大輔, 井手一郎, 村瀬洋, 藤吉弘亘

画像の認識・理解シンポジウム(MIRU) 2016.8.3

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

久徳遙矢, 川西康友, 出口大輔, 目加田慶人, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2016.8.4

Event date： 2016

Language：Japanese Presentation type：Poster presentation

Venue：アクトシティ浜松

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

先読み運転支援のための車載カメラからの「歩きスマホ」認識に関する検討

新村文郷, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 藤吉弘亘

画像の認識・理解シンポジウム(MIRU) 2016.8.4

A study on deep manifold embedding for object pose estimation

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

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

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

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

IEICE Technical Report (PRMU) 2016.9.5

Subjective Sensing of Real World Activity on Group Study International conference

Daisuke Deguchi, Kazuaki Kondo, Atsushi Shimada

18th International Conference on Collaboration Technologies (CollabTech2016) 2016.9.16

Event date： 2016

Language：English Presentation type：Poster presentation

Venue：しいのき迎賓館, 金沢市

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

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

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

IEICE Technical Report (MVE) 2016.10.13

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

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

IEICE Technical Report (MVE) 2016.10.13

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

Norimasa Kobori, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (IE) 2016.10.6

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