Faculty Profiles - Deguchi Daisuke

Papers - Deguchi Daisuke

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

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

Proceedings of 2012 IEEE Conference on Intelligent Transportation Systems (ITSC2012) page： 1321 - 1326 2012.9

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

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

Detection and classification of repetitious human motions combining shift variant and invariant features Reviewed

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

Proceedings of the 3rd International Conference on Emerging Security Technologies (EST2012) page： 86 - 89 2012.9

Robust Face Super-Resolution Using Free-Form Deformations For Low-Quality Surveillance Video Reviewed

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

Proceedings of 2012 IEEE International Conference on Multimedia and Expo (ICME2012) page： 368 - 373 2012.7

Speech shot extraction from broadcast news videos Reviewed

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

International Journal of Semantic Computing Vol. 6 ( 2 ) page： 179 - 204 2012.6

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

We propose a method for discriminating between a speech shot and a narrated shot to extract genuine speech shots from a broadcast news video. Speech shots in news videos contain a wealth of multimedia information of the speaker, and could thus be considered valuable as archived material. In order to extract speech shots 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 an approach, since news videos contain non-speech shots where the speaker is not the subject that appears in the screen, namely, narrated shots. To solve this problem, we propose a method to discriminate between a speech shot and a narrated shot in two stages. The first stage of the proposed method directly evaluates the inconsistency between a subject and a speaker based on the co-occurrence between lip motion and voice. The second stage of the proposed method evaluates based on the intra- and inter-shot features that focus on the tendency of speech shots. With the combination of both stages, the proposed method accurately discriminates between a speech shot and a narrated shot. In the experiments, the overall accuracy of speech shots extraction by the proposed method was 0.871. Therefore, we confirmed the effectiveness of the proposed method.

DOI： 10.1142/S1793351X12400077

Real-time marker-free patient registration for electromagnetic navigated bronchoscopy: a phantom study Reviewed

Daisuke Deguchi, Marco Feuerstein, Takayuki Kitasaka, Yasuhito Suenaga, Ichiro Ide, Hiroshi Murase, Kazuyoshi Imaizumi, Yoshinori Hasegawa, Kensaku Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 7 ( 3 ) page： 359 - 369 2012.5

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

Purpose
To perform bronchoscopy safely and smoothly, it is very important to develop a bronchoscopic guidance system. Transbronchial lung biopsy (TBLB) with a bronchoscopic guidance system especially should permit safe image-guided procedures. Recently, electromagnetic tracking (EMT) is utilized to track the tip of the bronchoscope camera in real time. For most tracking methods using position sensors, registration between tracking data and previously acquired reference image data, such as CT image, is performed using natural landmarks of the patient or fiducial markers attached to the patient, whose positions need to be measured manually by the physician before the actual bronchoscopy. Therefore, this paper proposes a marker-free CT-to-patient registration method utilizing bronchoscope's position and orientation obtained by the EMT.

Methods
We developed a guidance system that is able to track the tip of the bronchoscope camera in real time. In the case of a guidance system that uses position sensors, natural landmarks of the patient or fiducial markers attached to the patient are needed to obtain the correspondence between EMT outputs and previously acquired reference image data, such as CT image. This paper proposes a registration method without landmarks or fiducials by estimating the transformation matrix between the patient and the CT image taken prior to the bronchoscopic examination. This estimation is performed by computing correspondences between the outputs of the EMT sensor and airways extracted from the CT image. As ambiguities between EMT measurements and their corresponding airway branches may arise at airway bifurcations, we introduce a stable airway branch selection mechanism for improving the robustness of the estimation of the transformation matrix. To evaluate the performance of the proposed method, we applied the method to a rubber bronchial phantom and added virtual breathing motion to the sensor output.

Results
Experimental results show that the accuracy of our proposed method is within 2.0-3.0 mm (without breathing motion) and 2.5-3.5 mm (with breathing motion). The proposed method could also track a bronchoscope camera in real time.

Conclusions
We developed a method for CT-to-patient registration using a position sensor without fiducial markers and natural landmarks. Endoscopic guided biopsy of lung lesions is feasible using a marker-free CT-to-patient registration method.

DOI： 10.1007/s11548-011-0626-9

Construction of a local attraction map according to social visual attention Reviewed

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

Proceedings of the 5th International Conference on Intelligent Interactive Multimedia Systems and Services (IIMSS2012) page： 153 - 162 2012.5

Development and comparison of new hybrid motion tracking for bronchoscopic navigation Reviewed

Xiongbiao Luo, Marco Feuerstein, Daisuke Deguchi, Takayuki Kitasaka, Hirotsugu Takabatake, Kensaku Mori

Medical Image Analysis Vol. 16 ( 3 ) page： 577 - 596 2012.4

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

This paper presents a new hybrid camera motion tracking method for bronchoscopic navigation combining SIFT, epipolar geometry analysis, Kalman filtering, and image registration. In a thorough evaluation, we compare it to state-of-the-art tracking methods. Our hybrid algorithm for predicting bronchoscope motion uses SIFT features and epipolar constraints to obtain an estimate for inter-frame pose displacements and Kalman filtering to find an estimate for the magnitude of the motion. We then execute bronchoscope tracking by performing image registration initialized by these estimates. This procedure registers the actual bronchoscopic video and the virtual camera images generated from 3D chest CT data taken prior to bronchoscopic examination for continuous bronchoscopic navigation. A comparative assessment of our new method and the state-of-the-art methods is performed on actual patient data and phantom data. Experimental results from both datasets demonstrate a significant performance boost of navigation using our new method. Our hybrid method is a promising means for bronchoscope tracking, and outperforms other methods based solely on Kalman filtering or image features and image registration.

DOI： 10.1016/j.media.2010.11.001

Integration of generative learning and multiple pose classifiers for pedestrian detection Reviewed

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2012 Vol. 1 page： 567 - 572 2012.2

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

Recently, pedestrian detection from in-vehicle camera images is becoming an important technology in ITS (Intelligent Transportation System).
However, it is difficult to detect pedestrians stably due to the variety of their poses and their backgrounds.
To tackle this problem, we propose a method to detect various pedestrians from in-vehicle camera images by using multiple classifiers corresponding to various pedestrian pose classes.
Since pedestrians’ pose varies widely, it is difficult to construct a single classifier that can detect pedestrians with various poses stably.
Therefore, this paper constructs multiple classifiers optimized for variously posed pedestrians by classifying pedestrian images into multiple pose classes.
Also, to reduce the bias and the cost for preparing numerous pedestrian images for each pose class for learning, the proposed method employs a generative learning method.
Finally, the proposed method constructs multiple classifiers by using the synthesized pedestrian images.
Experimental results showed that the detection accuracy of the proposed method outperformed comparative methods, and we confirmed that the proposed method could detect variously posed pedestrians stably.

DOI： 10.5220/0003817305670572

Construction of an accurate traffic sign detector by automatic gathering of traffic sign images based on retrospective tracking Reviewed

Daisuke Deguchi, Keisuke Doman, Ichiro Ide, Hiroshi Murase

IEICE Transactions on Information and Systems Vol. J95-D ( 1 ) page： 76 - 84 2012.1

Improvement of Vehicle Ego-localization by Sequential Matching of Feature-points from an Aerial Image and an In-vehicle Camera Image Reviewed

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

IEICE Transactions on Information and Systems Vol. J95-D ( 1 ) page： 111 - 121 2012.1

Estimation of traffic sign visibility based on the integration of contrast features and appearance features Reviewed

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

IEICE Transactions on Information and Systems Vol. J95-D ( 1 ) page： 122 - 130 2012.1

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

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Papers - Deguchi Daisuke