研究者詳細 - 出口　大輔

論文 - 出口　大輔

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マルチメディア情報の補足による初心者向け料理レシピの作成へ向けて査読有り

志土地由香, 井手一郎, 中村裕一, 出口大輔, 高橋友和, 村瀬洋

電子情報通信学会論文誌 J94-A 巻 ( 7 ) 頁： 544 - 547 2011年7月

記述言語：日本語掲載種別：研究論文（学術雑誌）

既存のテキスト料理レシピから初心者に分かりにくい表現を検出した後，大量の料理レシピから抽出した情報に基づいてテキストを，調理動作の種類に応じて画像・映像を補足することで，分かりやすいマルチメディア料理レシピを作る方法を検討した．

On-road Obstacle Detection by Comparing Present and Past In-vehicle Camera Images 査読有り

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

Proceedings of IAPR Conference on Machine Vision Applications (MVA) 2011 頁： 357 - 360 2011年6月

Estimation of Traffic Sign Visibility Considering Temporal Environmental Changes for Smart Driver Assistance 査読有り

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

Proceedings of 2011 IEEE Intelligent Vehicles Symposium (IV2011) 頁： 667 - 672 2011年6月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

We propose a visibility estimation method for traffic signs considering temporal environmental changes, as a part of work for the realization of nuisance-free driver assistance systems. Recently, the number of driver assistance systems in a vehicle is increasing. Accordingly, it is becoming important to sort out appropriate information provided from them, because providing too much information may cause driver distraction. To solve such a problem, we focus on a visibility estimation method for controlling the information according to the visibility of a traffic sign. The proposed method sequentially captures a traffic sign by an in-vehicle camera, and estimates its accumulative visibility by integrating a series of instantaneous visibility. By this way, even if the environmental conditions may change temporally and complicatedly, we can still accurately estimate the visibility that the driver perceives in an actual traffic scene. We also investigate the performance of the proposed method and show its effectiveness.

Road Image Update using In-vehicle Camera Images and Aerial Image 査読有り

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

Proceedings of 2011 IEEE Intelligent Vehicles Symposium (IV2011) 頁： 460 - 465 2011年6月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

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

Proceedings of 2011 IEEE Intelligent Vehicles Symposium (IV2011) 頁： 290 - 295 2011年6月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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 査読有り

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

Proceedings of 2011 IEEE Intelligent Vehicles Symposium (IV2011) 頁： 72 - 77 2011年6月

担当区分：筆頭著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

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.

位置依存型識別器を用いた車載カメラ画像からの路面標示検出査読有り

野田雅文, 高橋友和, 出口大輔, 井手一郎, 村瀬洋, 小島祥子, 内藤貴志

電気学会論文誌D 131 巻 ( 4 ) 頁： 466 - 474 2011年4月

記述言語：日本語掲載種別：研究論文（学術雑誌）

In this study, we propose a method for detecting road markings recorded in an image captured by an in-vehicle camera by using a position-dependent classifier. Road markings are symbols painted on the road surface that help in preventing traffic accidents and in ensuring traffic smooth. Therefore, driver support systems for detecting road markings, such as a system that provides warning in the case when traffic signs are overlooked, and supporting the stopping of a vehicle are required. It is difficult to detect road markings because their appearance changes with the actual traffic conditions, e. g. the shape and resolution change. The variation in these appearances depend on the positional relation between the vehicle and the road markings, and on the vehicle posture. Although these variations are quite large in an entire image, they are relatively small in a local area of the image. Therefore, we try to improve the detection performance by taking into account the local variations in these appearances. We propose a method in which a position-dependent classifier is used to detect road markings recorded in images captured by an in-vehicle camera. Further, to train the classifier efficiently, we propose a generative learning method that takes into consideration the positional relation between the vehicle and road markings, and also the vehicle posture. Experimental results showed that the detection performance when the proposed method was used was better than when a method involving a single classifier was used.

DOI： 10.1541/ieejias.131.466

Accurate and Robust Attitude Estimation of a Moving Vehicle Using MEMS Gyroscopes and a Monocular Camera 査読有り

Norimasa Kobori, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

Proceedings of 2010 Workshop on Picture Coding and Image Processing (WPCIP 2010) 2010年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

In order to estimate accurate attitude of mobile robots and　vehicles, we propose a hybrid system which combines a lowcost　monocular camera with a gyro sensor. A gyro sensor has　drift errors that accumulate over time. On the other hand, a　camera cannot obtain the rotation continuously in the case　where feature points cannot be extracted from images, although　the accuracy is better than a gyro sensor. To solve　these problems, we propose a method for combining these　sensors based on an Extended Kalman Filter.

拡張DPマッチングを用いた視野角の異なるカメラ映像間の時空間対応付けによる自車位置推定査読有り

内山寛之, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

電子情報通信学会論文誌 J93-D 巻 ( 12 ) 頁： 2659 - 2665 2010年12月

記述言語：日本語掲載種別：研究論文（学術雑誌）

本論文では，データベース作成時に全方位カメラ，位置推定時に通常カメラを使用するアピアランスベースの自車位置推定手法を提案する．従来のアピアランスベースの自車位置推定では，データベース作成時と位置推定時で同一種類のカメラが使用されることが多い．しかし，位置推定精度やカメラの設置位置の制約などの点で問題となることがある．提案手法では，通常カメラ映像のフレームに対応する全方位カメラ映像のフレームと，そのフレーム中の領域を探索する．しかし，市街地では類似する物体が多く存在し，単一フレーム照合では正確な照合が難しい．そのため，複数フレーム照合を用いることで精度の向上を図る必要がある．これを実現するため，フレームと領域を考慮した映像間の照合コストを定式化する．そして，動的計画法によりこれを最小化するためのアルゴリズムを導入し，このアルゴリズムを用いて映像全体で最適に対応づける．データベース内のフレームには位置情報が付加されており，これにより自車位置を得る．実際に市街地で撮影した映像を用いた評価実験の結果，自車位置推定誤差が2m以下の割合が，領域の対応付けを行わない手法で77%，提案手
法で90%であり，提案手法の有効性を確認した．

Multimedia supplementation to a cooking recipe text for facilitating its understanding to inexperienced users 査読有り

Ichiro Ide, Yuka Shidochi, Yuichi Nakamura, Daisuke Deguchi, Tomokazu Takahashi, Hiroshi Murase

Proceedings of the 2nd Workshop on Cooking and Eating Activities (CEA2010) 頁： 242 - 247 2010年12月

Frontal Face Generation from Multiple Low-Resolution Non-Frontal Faces for Face Recognition 査読有り

Yuki Kono, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of the 10th International Workshop on Visual Surveillance 2010 2010年11月

Improvement of a traffic sign detector by retrospective gathering of training samples from in-vehicle camera image sequences 査読有り

Daisuke Deguchi, Keisuke Doman, Ichiro Ide, Hiroshi Murase

Proceedings of Computer Vision in Vehicle Technology: From Earth to Mars (CVVT2010) 2010年11月

Vehicle Ego-localization by Matching In-vehicle Camera Images to an Aerial Image 査読有り

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

Proceedings of Computer Vision in Vehicle Technology: From Earth to Mars (CVVT2010) 2010年11月

Marker-Free Registration for Electromagnetic Navigation Bronchoscopy under Respiratory Motion

Marco Feuerstein, Takamasa Sugiura, Daisuke Deguchi, Tobias Reichl, Takayuki Kitasaka, Kensaku Mori

Proceedings of the 5th International Workshop on Medical Imaging and Augmented Reality (MIAR2010) LNCS 6326 巻頁： 237 - 246 2010年9月

色変動を考慮した生成型学習法による道路標識検出器の構築査読有り

道満恵介, 出口大輔, 高橋友和, 目加田慶人, 井手一郎, 村瀬洋

電子情報通信学会論文誌 J93-D 巻 ( 8 ) 頁： 1375 - 1385 2010年8月

記述言語：日本語掲載種別：研究論文（学術雑誌）

環境変化に対してロバストかつ高速な物体検出を可能とする識別器として，Violaらが提案したカスケード型識別器がある．これを用いて様々な環境下に存在する道路標識を高精度に検出するためには，多様な見えの変動を含んだ大量の標識画像を用いて識別器の学習を行う必要がある．しかしながら，多様な見えの変動をバランスよく含んだ大量の標識画像を手作業で収集するには多大なコストがかかる．そのため，本研究では生成型学習を用いてカスケード型識別器を構築することを考える．これまでにも生成型学習を用いて識別器を構築
する手法は提案されているが，形状やテクスチャの変動のみが考慮されており，色の変動は考慮されていない．
そこで本論文では，形状やテクスチャの変動に加えて色の変動も考慮し，より高い検出性能をもったカスケード型識別器を構築する手法を提案する．車載カメラ映像を用いた道路標識の検出実験の結果，本論文で提案する色の変動を考慮する生成型学習により，従来よりも高い検出性能をもつカスケード型識別器が構築できることを確認した．

Removal of Moving Objects from a Street-View Image by Fusing Multiple Image Sequences 査読有り

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

Proceedings of the 20th IAPR International Conference on Pattern Recognition (ICPR2010) 頁： 3456 - 3459 2010年8月

Classification of near-duplicate video segments based on their appearance patterns 査読有り

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

Proceedings of the 20th IAPR International Conference on Pattern Recognition (ICPR2010) 頁： 3129 - 3133 2010年8月

Estimation of Traffic Sign Visibility Toward Smart Driver Assistance 査読有り

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yukimasa Tamatsu

Proceedings of 2010 IEEE Intelligent Vehicles Symposium (IV2010) 頁： 45 - 50 2010年6月

Construction of cascaded traffic sign detector using generative learning 査読有り

Keisuke Doman, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

Proceedings of the 4th International Conference on Innovative Computing, Information and Control (ICICIC2009) 2009年12月

Labeling News Topic Threads with Wikipedia Entries 査読有り

Tomoki Okuoka, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of the 1st International Workshop on Content-Based Audio/Video Analysis for Novel TV Services (CBTV2009) 頁： 501 - 504 2009年12月

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