Faculty Profiles - Deguchi Daisuke

Presentations -

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Extraction of Tips on Taste in Supplementary Information of Cooking Recipes

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

IEICE Technical Report (MVE) 2013.3.11

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

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

IEICE Technical Report (MVE) 2013.3.11

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

Toru Kotsuka, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

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

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

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

IEICE Technical Report (PRMU) 2013.12.12

Localization of point heat sources using a low resolution infrared sensor array

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

IEICE Technical Report (PRMU) 2013.12.12

Exemplar-Based Super-Resolution of Human Body Image in Surveillance Video

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

Vision Engineering Workshop (ViEW) 2013 2013.12.5

監視カメラシステムのための低解像度人体画像の超解像に関する検討

西堀研人, 高橋友和, 出口大輔, 井手一郎, 村瀬洋

計測自動制御学会システム・情報部門学術講演会（SSI） 2013.11.18

Event date： 2013

Language：Japanese Presentation type：Poster presentation

Venue：滋賀県・大津・ピアザ淡海

防犯を目的とした監視カメラの設置が増えてきており，不審者の検出や人物照合等に用いられている．このような広域を監視するカメラを用いた場合，人物は低解像度で撮影されることが多く人物の照合が困難となる．低解像度画像を高解像度化する技術として，超解像技術が用いられている．しかし，人体の画像は姿勢や服装のように外見の変化が大きく超解像が困難である．そこで，本研究では低解像度の人体画像を高解像度化することで，人が見ても機械が処理をしても人物照合をより正確に行うことができる高解像度の人体画像を生成することを目的とする．ここでは，大量の人物画像からなる学習用画像を用いて1枚の低解像度画像から高解像度画像を生成する学習型超解像方式を適用し，人体画像の超解像について検討を行う．

Scene dependent classifiers for pedestrian detection International conference

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

International Joint Workshop on Advanced Sensing / Visual Attention and Interaction (ASVAI2013) 2013.11.5

Automatic authoring of a domestic cooking video based on the description of cooking instructions International conference

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

5th International Workshop on Multimedia for Cooking and Eating Activities (CEA'13) 2013.10.21

Blur-invariant Traffic Sign Recognition Using Compact Local Phase Quantization International conference

Saleh Aly, Daisuke Deguchi, Hiroshi Murase

2013 IEEE Conference on Intelligent Transportation Systems (ITSC2013) 2013.10.8

Construction of a traffic sign detector based on voting type co-training International conference

Yuji Kojima, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

2013 IEEE Conference on Intelligent Transportation Systems (ITSC2013) 2013.10.8

A study on people density estimation using multiple cameras

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

IEICE Technical Report (PRMU) 2013.10.3

Prediction of Pedestrian Detectability for Drivers by Image Processing and its Driver Adaptation International conference

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

6th Biennial Workshop on Digital Signal Processing for In-Vehicle Systems (DSP2013) 2013.9.30

Event date： 2013

Language：English Presentation type：Oral presentation (general)

Venue：Korea University, Seoul, Korea

In recent years, advances in pedestrian detection technology have resulted in the development of driving assistance systems that notify the drivers of the presence of pedestrians. However, warning of all of the presence of pedestrians would confuse the driver. Therefore, the driver should only be notified of the less detectable pedestrians to avoid confusion. To achieve this, it is necessary to develop a method to predict the driver’s perception performance of pedestrian detectability. This paper proposes a method that predicts the pedestrian detectability considering the difference between individual drivers. The proposed method constructs a predictor specific to each driver, in order to predict the pedestrian detectability precisely. To obtain the ground truth of the pedestrian detectability, we conducted an experiment by human subjects using images from an in-vehicle camera including pedestrians. From the comparison between the output of the proposed method and the actual detectability, we confirmed that the proposed method significantly reduces the prediction error in comparison with the existing methods.

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

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

IEICE Technical Report (MVE) 2013.9.26

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

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

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

Sakaiを中心とした教育基盤構築の現状と今後の展開

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

大学ICT推進協議会（AXIES） 2012.12.17

A Collaborative Report on The 13th Sakai Conference

Yuji Tokiwa, Makoto Miyazaki, Ryuichi Matsuba, Daisuke Deguchi, Shoji Kajita

IPSJ SIG Technical Report (CLE) 2012.11.3

Subtraction-Based Forward Obstacle Detection Using Illumination Insensitive Feature for Driving-Support International conference

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

Computer Vision in Vehicle Technology: From Earth to Mars (CVVT2012) 2012.10.13

Event date： 2012

Language：English Presentation type：Oral presentation (general)

Venue：Firenze, Italy

This paper proposes a method for detecting general obstacles on a road by subtracting present and past in-vehicle camera images.
The image-subtraction-based object detection approach can be applied to detect any kind of obstacles although the existing learning-based methods detect only specific obstacles.
To detect general obstacles, the proposed method first computes a frame-by-frame correspondence between the present and the past in-vehicle camera image sequences, and then registrates road surfaces between the frames.
Finally, obstacles are detected by applying image subtraction to the registrated road surface regions with an illumination insensitive feature for robust detection.
Experiments were conducted by using several image sequences captured by an actual in-vehicle camera to confirm the effectiveness of the proposed method.
The experimental results shows that the proposed method can detect general obstacles accurately at a distance enough to avoid them safely even in situations with different illuminations.

DOI： 10.1007/978-3-642-33868-7_51

Visibility Estimation of Traffic Signals under Rainy Weather Conditions for Smart Driving Support International conference

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

2012 IEEE Conference on Intelligent Transportation Systems (ITSC2012) 2012.9.19

Event date： 2012

Language：English Presentation type：Oral presentation (general)

Venue：Anchorage, Alaska, USA,

The aim of this work is to support a driver by
notifying the information of traffic signals in accordance with
their visibility. To avoid traffic accidents, the driver should
detect and recognize surrounding objects, especially traffic
signals. However, when driving a vehicle under rainy weather
conditions, it is difficult for drivers to detect or to recognize
objects existing in the road environment in comparison with fine
weather conditions. Therefore, this paper proposes a method
for estimating the visibility of traffic signals for drivers under
rainy weather conditions by image processing. The proposed
method is based on the concept of visual noise known in the
field of cognitive science, and extracts two types of visual noise
features which ware considered that they affect the visibility of
traffic signals. We expect to improve the accuracy of visibility
estimation by combining the visual noise features with the
texture feature introduced in a previous work. Experimental
results showed that the proposed method could estimate the
visibility of traffic signals more accurately under rainy weather
conditions.

DOI： 10.1109/ITSC.2012.6338838

A preliminary study on a pedestrian detector adaptive to the driving environment using an in-vehicle camera

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

IEICE Technical Report (PRMU) 2012.9.3

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