Faculty Profiles - Deguchi Daisuke

Presentations -

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Road Image Update using In-vehicle Camera Images and Aerial Image International conference

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

2011 IEEE Intelligent Vehicles Symposium (IV2011) 2011.6.7

Event date： 2011

Language：English Presentation type：Poster presentation

Venue：Baden-Baden, Germany

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 International conference

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

2011 IEEE Intelligent Vehicles Symposium (IV2011) 2011.6.6

Event date： 2011

Language：English Presentation type：Poster presentation

Venue：Baden-Baden, Germany

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 International conference

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

2011 IEEE Intelligent Vehicles Symposium (IV2011) 2011.6.6

Event date： 2011

Language：English Presentation type：Poster presentation

Venue：Baden-Baden, Germany

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.

GPGPUによる高速画像処理

出口大輔

日本ロボット学会ロボット工学セミナー第62回シンポジウム「ロボットに使える画像処理技術の最前線」 2011.5.30

Event date： 2011

Language：Japanese Presentation type：Oral presentation (general)

Venue：東京大学武田先端知ビル5F 武田ホール

GPUを汎用計算に利用しようという試みであるGPGPU（General Purpose computing on GPUs）は，近年のGPUの高性能化およびその入手しやすさという特徴から，幅広い分野で高速計算に利用されるようになってきた．一方，画像処理アルゴリズムの多くは並列計算可能なものが多く，少しアルゴリズムを工夫することでCPUの数十倍の高速化を達成できるものも多く存在する．そこで，本講演ではGPGPUを手軽に利用できるCUDAを開発環境として利用し，実例を交えながら計算コストの高い画像処理を簡単に高速化できることを示す．

A Study on Road Image Generation by Mosaicing of In-Vehicle Camera Images Using Aerial Image as a Reference

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

IEICE Technical Report (PRMU) 2011.5.20

Road-image Map Construction Using Low-resolution Aerial Image and In-vehicle Camera Images

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

Vision Engineering Workshop (ViEW) 2011 2011.12.9

PRMU Algorithm Contest 2010 "Lock on targets! - object tracking -"

Daisuke Deguchi, Hiroshi Murase, Kazuaki Umeda, Masataka Saito, Kenichiro Fuji, Shingo Yamashita, Yuki Suetsugu, Syota Takai, Ryuta Sato, Takuma Maruyama

IEICE Technical Report (PRMU) 2011.3

Pedestrian Detection from In-vehicle Camera Images using Scene Context Information

Daisuke Hamada, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

2011 IEICE General Conference 2011.3

Pedestrian Detection with Generative Learning Method Considering Varying Pose

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

2011 IEICE General Conference 2011.3

Person Re-identification at a Room Entrance by Adaptive Feature Selection

Takuya Honda, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2011.3

Proposal of a Sight-seeing Map with Visual Classification and Presentation of Photos on the Web

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

IEICE Technical Report (MVE) 2011.3

Scene Segmentation of a Wedding Party Video by Scenario-based Matching with Example Videos

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

IEICE Technical Report (MVE) 2011.3

Study on super-resolution under facial pose variation for low-resolution face recognition

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

2011 IEICE General Conference 2011.3

Summarizing sports video by on-the-spot comments on Twitter

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

IEICE Technical Report (MVE) 2011.3

Summarizing sports video by on-the-spot comments on Twitter

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

2011.3

Video-based Generic Object Recognition by Combining Motion Features and BoF

Shogo Nakamura, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

IEICE Technical Report (PRMU) 2011.1.21

Quantification of the Visibility of Pedestrians Based on Integration of Local and Global Features

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

IEICE Technical Report (PRMU) 2011.1

A study on a method for stable pedestrian detection against pose changes with generative learning

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

IEICE Technical Report (PRMU) 2011.5.20

Advertisements on Urban Structures by Augmented Reality

Hiroyuki Uchiyama, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takahito Kawanishi, Kunio Kashino

Vision Engineering Workshop (ViEW) 2011 2011.12.9

Multi-frame super-resolution for low resolution QR-code recognition

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

Vision Engineering Workshop (ViEW) 2011 2011.12.9

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