Faculty Profiles - Deguchi Daisuke

Presentations -

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

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

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

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

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

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

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

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

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

Event date： 2014

Language：English Presentation type：Oral presentation (general)

Venue：Zurich, Switzerland

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

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

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

TransifexによるSakai 翻訳環境の設定

出口大輔

Ja Sakai アンカンファレンス 2014.9.4

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

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

IEICE Technical Report (PRMU) 2014.9.2

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

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

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

Event date： 2014

Language：English Presentation type：Poster presentation

Venue：Stockholm, Sweden

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

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

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

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

Baggage detection from multi-viewpoints human images

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

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

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

久徳遙矢, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2014.7.29

車両部位の検出数と検出信頼度を利用した回帰による車両台数推定

新村文郷, 出口大輔, 井手一郎, 村瀬洋

画像の認識・理解シンポジウム(MIRU) 2014.7.29

Human tracking via thermo-spatial sensitive histogram

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

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

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

Toru Kotsuka, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

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

A Collaborative Report on The Open Apereo 2013 Conference

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

IPSJ SIG Technical Report (CLE) 2013.12.15

複数フレーム型と学習型の組み合わせによる低解像度顔画像の超解像

吉田智成, 高橋友和, 出口大輔, 井手一郎, 村瀬洋

動的画像処理実利用化ワークショップ(DIA) 2013.3.7

Event date： 2013

Language：Japanese Presentation type：Oral presentation (general)

Venue：静岡大学浜松キャンパス

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

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

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

Dynamic Image Processing for Real Application workshop (DIA2013) 2013.3.7

Pedestrian detection with iterative generative learning

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

Dynamic Image Processing for Real Application workshop (DIA2013) 2013.3.7

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

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

Lecture Note in Computer Science 2013.1.9

Event date： 2013

Language：English Presentation type：Poster presentation

Venue：黄山柏瑞酒店（中華人民共和国安徽省黄山市）

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

DOI： 10.1007/978-3-642-35728-2_35

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

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

International Workshop on Advanced Image Technology (IWAIT) 2013 2013.1.8

Event date： 2013

Language：English Presentation type：Oral presentation (general)

Venue：Nagoya University

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

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

Daisuke Deguchi, Hiroshi Murase

International Workshop on Advanced Image Technology (IWAIT) 2013 2013.1.7

Event date： 2013

Language：English Presentation type：Oral presentation (general)

Venue：Nagoya University, Japan

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

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

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

IEICE Technical Report (PRMU) 2013.12.13

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