Faculty Profiles - Deguchi Daisuke

Papers - Deguchi Daisuke

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Classification of near-duplicate video clips in a large-scale broadcast video archive based on their appearance patterns Reviewed

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

Journal of Information Processing Vol. 52 ( 12 ) page： 3593 - 3598 2011.12

Creation of a Sight-seeing Map with Visual Classification of Photos on the Web Reviewed

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

Journal of Information Processing Vol. 52 ( 12 ) page： 3588 - 3592 2011.12

Detection of Inconsistency between Subject and Speaker based on the Co-occurrence of Lip Motion and Voice Towards Speech Scene Extraction from News Videos Reviewed

Shogo Kumagai, Keisuke Doman, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of 2011 IEEE International Symposium on Multimedia (ISM2011) page： 311 - 318 2011.12

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

We propose a method to detect the inconsistency between a subject and the speaker for extracting speech scenes from news videos.
Speech scenes in news videos contain a wealth of multimedia information, and are valuable as archived material.
In order to extract speech scenes from news videos, there is an approach that uses the position and size of a face region.
However, it is difficult to extract them with only such approach, since news videos contain non-speech scenes where the speaker is not the subject, such as narrated scenes.
To solve this problem, we propose a method to discriminate between speech scenes and narrated scenes based on the co-occurrence between a subject's lip motion and the speaker's voice.
The proposed method uses lip shape and degree of lip opening as visual features representing a subject's lip motion, and uses voice volume and phoneme as audio feature representing a speaker's voice.
Then, the proposed method discriminates between speech scenes and narrated scenes based on the correlations of these features.
We report the results of experiments on videos captured in a laboratory condition and also on actual broadcast news videos.
Their results showed the effectiveness of our method and the feasibility of our research goal.

Detection of Repetitive Cooking Motions in a Cooking Video Reviewed

Taku Kuhara, Daisuke Deguchi, Tomokazu Takahashi, Ichiro Ide, Hiroshi Murase

IEICE Transactions on Information and Systems Vol. J94-D ( 12 ) page： 1983 - 1985 2011.12

Generation of an In-Vehicle Camera Image Sequence without Temporary Objects by Selection of Partial Images from Multiple Image Sequences Reviewed

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

IEICE Transactions on Information and Systems Vol. J94-D ( 12 ) page： 2093 - 2104 2011.12

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

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

Proceedings of the 19th ACM International Multimedia Conference (ACM-MM2011) page： 1545 - 1548 2011.12

Accurate and Robust Attitude Estimation using MEMS Gyroscopes and a Monocular Camera Reviewed

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

Transactions of the Society of Instrument and Control Engineers Vol. 47 ( 10 ) page： 442 - 449 2011.10

Low resolution QR-code recognition by applying super-resolution using the property of QR-codes Reviewed

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

Proceedings of the 11th International Conference on Document Analysis and Recognition (ICDAR2011) page： 992 - 996 2011.9

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

This paper proposes a method for low resolution QR-code recognition. A QR-code is a two-dimensional binary symbol that can embed various information such as characters and numbers. To recognize a QR-code correctly and stably,the resolution of an input image should be high. In practice,however, recognition of a QR-code is usually difficult due to
low resolution when it is captured from a distance. In this paper, we propose a method to improve the performance of low resolution QR-code recognition by using the super-resolution technique that generates a high resolution image from multiple low-resolution images. Although a QR-code is a binary pattern, it is observed as a grayscale image due to the degradation through the capturing process. Especially the pixels around the borders between white and black regions become ambiguous. To overcome this problem, the proposed method introduces a binary pattern constraint to generate super-resolved images appropriate for recognition. Experimental results showed that a recognition rate of 98% an be achieved by the proposed method, which is a 15.7% improvement in comparison with a method using a conventional super-resolution method.

Power-efficient hardware architecture of K-Means clustering with Bayesian-Information-Criterion processor for multimedia processing applications Reviewed

Tse-Wei Chen, Chih-Hao Sun, Hsiao-Hang Su, Shao-Yi Chien, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Vol. 1 ( 3 ) page： 357 - 368 2011.9

Language：English Publishing type：Research paper (scientific journal)

A power-efficient K-Means hardware architecture that can automatically estimate the number of clusters in the clustering process is proposed. The contributions of this work include two main aspects. The first is the integration of the hierarchical data sampling in the hardware to accelerate the clustering speed. The second is the development of the Bayesian-Information-Criterion (BIC) Processor" to estimate the number of clusters of K-Means. The architecture of the "BIC Processor" is designed based on the simplification of the BIC computations, and the precision of the logarithm function is also analyzed. The experiments show that the proposed architecture can be employed in different multimedia applications, such as motion segmentation and edge-adaptive noise reduction. Besides, the gate count of the hardware is 51 K with the 90-nm complimentary metal-oxide-semiconductor technology. It is also shown that this work can achieve high efficiency compared with a GPU, and the power consumption scales well with the number of clusters and the number of dimensions. The power consumption ranges between 10.72 and 12.95 mW in different modes when the operating frequency is 233 MHz."

DOI： 10.1109/JETCAS.2011.2165231

Towards the Creation of a Cooking Recipe for Inexperienced Users by Supplementing Multimedia Information Reviewed

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

IEICE Transactions on Information and Systems Vol. J94-A ( 7 ) page： 544 - 547 2011.7

On-road Obstacle Detection by Comparing Present and Past In-vehicle Camera Images Reviewed

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

Proceedings of IAPR Conference on Machine Vision Applications (MVA) 2011 page： 357 - 360 2011.6

Estimation of Traffic Sign Visibility Considering Temporal Environmental Changes for Smart Driver Assistance Reviewed

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

Proceedings of 2011 IEEE Intelligent Vehicles Symposium (IV2011) page： 667 - 672 2011.6

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

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 Reviewed

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

Proceedings of 2011 IEEE Intelligent Vehicles Symposium (IV2011) page： 460 - 465 2011.6

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

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 Reviewed

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

Proceedings of 2011 IEEE Intelligent Vehicles Symposium (IV2011) page： 290 - 295 2011.6

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

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 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

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

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

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Papers - Deguchi Daisuke