Faculty Profiles - Deguchi Daisuke

Papers - Deguchi Daisuke

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Intelligent Traffic Sign Detector: Adaptive Learning Based on Online Gathering of Training Samples Reviewed

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

Proceedings of 2011 IEEE Intelligent Vehicles Symposium (IV2011) page： 72 - 77 2011.6

Authorship：Lead author Language：English Publishing type：Research paper (international conference proceedings)

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.

Detection of Road Markings Recorded in In-Vehicle Camera Images by Using Position-Dependent Classifiers Reviewed Open Access

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

IEEJ Transactions on Industry Applications Vol. 131 ( 4 ) page： 466 - 474 2011.4

Accurate and Robust Attitude Estimation of a Moving Vehicle Using MEMS Gyroscopes and a Monocular Camera Reviewed

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

Proceedings of 2010 Workshop on Picture Coding and Image Processing (WPCIP 2010) 2010.12

Language：English Publishing type：Research paper (international conference proceedings)

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.

Ego-Localization by Spatio-Temporal Matching between Videos Obtained from Cameras with Different Viewing Angles Using an Extended DTW Method Reviewed Open Access

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

IEICE Transactions on Information and Systems Vol. J93-D ( 12 ) page： 2659 - 2665 2010.12

Multimedia supplementation to a cooking recipe text for facilitating its understanding to inexperienced users Reviewed

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

Proceedings of the 2nd Workshop on Cooking and Eating Activities (CEA2010) page： 242 - 247 2010.12

Frontal Face Generation from Multiple Low-Resolution Non-Frontal Faces for Face Recognition Reviewed

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

Proceedings of the 10th International Workshop on Visual Surveillance 2010 2010.11

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

Daisuke Deguchi, Keisuke Doman, Ichiro Ide, Hiroshi Murase

Proceedings of Computer Vision in Vehicle Technology: From Earth to Mars (CVVT2010) 2010.11

Vehicle Ego-localization by Matching In-vehicle Camera Images to an Aerial Image Reviewed

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) 2010.11

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) Vol. LNCS 6326 page： 237 - 246 2010.9

Construction of a traffic sign detector using generative learning method considering color variation Reviewed Open Access

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

IEICE Transactions on Information and Systems Vol. J93-D ( 8 ) page： 1375 - 1385 2010.8

Removal of Moving Objects from a Street-View Image by Fusing Multiple Image Sequences Reviewed Open Access

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

Proceedings of the 20th IAPR International Conference on Pattern Recognition (ICPR2010) page： 3456 - 3459 2010.8

Classification of near-duplicate video segments based on their appearance patterns Reviewed Open Access

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

Proceedings of the 20th IAPR International Conference on Pattern Recognition (ICPR2010) page： 3129 - 3133 2010.8

Estimation of Traffic Sign Visibility Toward Smart Driver Assistance Reviewed Open Access

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

Proceedings of 2010 IEEE Intelligent Vehicles Symposium (IV2010) page： 45 - 50 2010.6

Construction of cascaded traffic sign detector using generative learning Reviewed

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) 2009.12

Labeling News Topic Threads with Wikipedia Entries Reviewed

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) page： 501 - 504 2009.12

Automated Anatomical Labeling of Bronchial Branches Extracted from CT Datasets Based on Machine Learning and Combination Optimization and Its Application to Bronchoscope Guidance Reviewed

Kensaku Mori, Shunsuke Ota, Daisuke Deguchi, Takayuki Kitasaka, Yasuhito Suenaga, Shingo Iwano, Yoshinori Hasegawa, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2009) Vol. LNCS 5762, Part II page： 707 - 714 2009.9

Language：English Publishing type：Research paper (international conference proceedings)

This paper presents a method for the automated anatomical labeling of bronchial branches extracted from 3D CT images based on machine learning and combination optimization. We also show applications of anatomical labeling on a bronchoscopy guidance system. This paper performs automated labeling by using machine learning and combination optimization. The actual procedure consists of four steps: (a) extraction of tree structures of the bronchus regions extracted from CT images, (b) construction of AdaBoost classifiers, (c) computation of candidate names for all branches by using the classifiers, (d) selection of best combination of anatomical names. We applied the proposed method to 90 cases of 3D CT datasets. The experimental results showed that the proposed method can assign correct anatomical names to 86.9% of the bronchial branches up to the sub-segmental lobe branches. Also, we overlaid the anatomical names of bronchial branches on real bronchoscopic views to guide real bronchoscopy.

DOI： 10.1007/978-3-642-04271-3_86

Low-resolution Character Recognition by Video-based Super-resolution Reviewed

大倉直, 出口大輔, 高橋友和, 井手一郎, 村瀬洋

Proceedings of the 10th International Conference on Document Analysis and Recognition (ICDAR2009) page： 191 - 195 2009.7

Selective image similarity measure for bronchoscope tracking based on image registration Reviewed

Daisuke Deguchi, Kensaku Mori, Marco Feuerstein, Takayuki Kitasaka, Calvin R. Maurer Jr., Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Medical Image Analysis Vol. 13 ( 4 ) page： 621 - 633 2009.6

Authorship：Lead author Language：English Publishing type：Research paper (scientific journal)

We propose a selective method of measurement for computing image similarities based on characteristic structure extraction and demonstrate its application to flexible endoscope navigation, in particular to a bronchoscope navigation system. Camera motion tracking is a fundamental function required for image-guided treatment or therapy systems. In recent years, an ultra-tiny electromagnetic sensor commercially became available, and many image-guided treatment or therapy systems use this sensor for tracking the camera position and orientation. However, due to space limitations, it is difficult to equip the tip of a bronchoscope with such a position sensor, especially in the case of ultra-thin bronchoscopes. Therefore, continuous image registration between real and virtual bronchoscopic images becomes an efficient tool for tracking the bronchoscope. Usually, image registration is done by calculating the image similarity between real and virtual bronchoscopic images. Since global schemes to measure image similarity, such as mutual information, squared gray-level difference, or cross correlation, average differences in intensity values over an entire region, they fail at tracking of scenes where less characteristic structures can be observed. The proposed method divides an entire image into a set of small subblocks and only selects those in which characteristic shapes are observed. Then image similarity is calculated within the selected subblocks. Selection is done by calculating feature values within each subblock. We applied our proposed method to eight pairs of chest X-ray CT images and bronchoscopic video images. The experimental results revealed that bronchoscope tracking using the proposed method could track up to 1600 consecutive bronchoscopic images (about 50s) without external position sensors. Tracking performance was greatly improved in comparison with a standard method utilizing squared gray-level differences of the entire images.

DOI： 10.1016/j.media.2009.06.001

An improved method for automated recognition of bronchial tree structure by optimizing combinations of candidate anatomical names Reviewed

Takayuki Kitasaka, Shunsuke Ota, Daisuke Deguchi, Kensaku Mori, Yasuhito Suenaga, Yoshinori Hasegawa, Kazuyoshi Imaizumi, Shingo Iwano, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

International Journal of Computer Assisted Radiology and Surgery Vol. 4 page： 327 - 328 2009.6

Ego-localization using Streetscape Image Sequences from In-vehicle Cameras Reviewed Open Access

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

Proceedings of 2009 IEEE Intelligent Vehicles Symposium (IV2009) page： 185 - 190 2009.6

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Papers - Deguchi Daisuke