Faculty Profiles - Deguchi Daisuke

Papers - Deguchi Daisuke

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Analysis of Effective Flicker Light Patterns to Improve the Pedestrian Detectability from a Driver for an Intelligent Headlight System Reviewed Open Access

Takashi Maeda, Takatsugu Hirayama, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Journal of the Japan Society for Precision Engineering Vol. 85 ( 12 ) page： 1157 - 1162 2019.12

Cyclist Recognition via Size-Adaptable PointNet Reviewed Open Access

Taiki Yamamoto, Fumito Shinmura, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Kazuki Kato, Hiroshi Murase

Journal of the Japan Society for Precision Engineering Vol. 85 ( 12 ) page： 1117 - 1126 2019.12

Scene-Adaptive Driving Area Prediction based on Automatic Label Acquisition from Driving Information Reviewed

Takuya Migishima, Haruya Kyutoku, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

Proceedings of the 5th IAPR Asian Conference on Pattern Recognition (ACPR2019) 2019.11

Semantic Segmentation of Railway Images Considering Temporal Continuity Reviewed

Yuki Furitsu, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase, Hiroki Mukoujima, Nozomi Nagamine

Proceedings of the 5th IAPR Asian Conference on Pattern Recognition (ACPR2019) 2019.11

An Analysis of How Driver Experience Affects Eye-Gaze Behavior for Robotic Wheelchair Operation Reviewed

Yamato Maekawa, Naoki Akai, Takatsugu Hirayama, Luis Yoichi Morales, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

Proceedings of 2019 IEEE International Conference on Computer Vision (ICCV) Workshops page： 4443 - 4451 2019.11

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

Drivers obtain information on surrounding environment using their eyesights. Experienced eye-gaze behavior is needed when driving at places where multiple risks exist to prepare for and avoid them. In this work, we analyze the change in eye-gaze behavior in such situations while a driver gains experience on the operation of a robotic wheelchair. Accurate distance information in the traffic environment is important to analyze the eye-gaze behavior. However, almost all previous works analyze eye-gaze behavior in a 2D environment, so they could not obtain accurate distance information. For this reason, we analyze eye-gaze behavior in 3D space. Concretely, we developed a novel eye-gaze behavior analysis platform based on a robotic wheelchair and estimated the driver's attention in 3D space. We try to analyze the eye-gaze behavior considering a useful field-of-view in 3D space based on the distance information instead of only the fixation point to investigate the objects that a driver implicitly pays attention to and from where s/he focuses on them. Results show that novice drivers pay attention to a single risk at a time. In contrast, they pay more attention to multiple risks simultaneously as they gain experience. Additionally, we discuss what features are effective to model the eye-gaze behavior based on the results.

DOI： 10.1109/ICCVW.2019.00545

Exemplar-based Pseudo-Viewpoint Rotation for White-Cane User Recognition from a 2D Human Pose Sequence Reviewed

Naoki Nishida, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Jun Piao

2019.9

Similar Seasonal-Geo-Region Mining based on Visual Concepts in Social Media Photos Reviewed

Yasutomo Kawanishi, Ichiro Ide, Chen Lu, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

Proceedings of the 5th IEEE Conference on Multimedia BigData page： 86 - 93 2019.9

Estimation of the attractiveness of food photography based on image features Reviewed Open Access

Kazuma Takahashi, Tatsumi Hattori, Keisuke Doman, Yasutomo Kawanishi, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Trans. on Information and Systems Vol. E102-D ( 8 ) page： 1590 - 1593 2019.8

Hand Orientation Estimation in Probability Density Form

Kazuaki Kondo, Daisuke Deguchi, Atsushi Shimada

2019.6

Estimating the Imageability of a sentence for image caption evaluation

Kazuki Umemura, Marc Aurel Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

2019.4

Estimating the visual variety of concepts by referring to Web popularity Reviewed

Marc Aurel Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Daisuke Deguchi, Hiroshi Murase

Multimedia Tools and Applications Vol. 78 ( 7 ) page： 9463 - 9488 2019.4

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

Increasingly sophisticated methods for data processing demand knowledge on the semantic relationship between language and vision. New fields of research like Explainable AI demand to step away from black-boxed approaches and understanding how the underlying semantics of data sets and AI models work. Advancements in Psycholinguistics suggest, that there is a relationship from language perception to how language production and sentence creation work. In this paper, a method to measure the visual variety of concepts is proposed to quantify the semantic gap between vision and language. For this, an image corpus is recomposed using ImageNet and Web data. Web-based metrics for measuring the popularity of sub-concepts are used as a weighting to ensure that the image composition in a dataset is as natural as possible. Using clustering methods, a score describing the visual variety of each concept is determined. A crowd-sourced survey is conducted to create ground-truth values applicable for this research. The evaluations show that the recomposed image corpus largely improves the measured variety compared to previous datasets. The results are promising and give additional knowledge about the relationship of language and vision.

DOI： 10.1007/s11042-018-6528-x

Person Re-Detection from an In-Vehicle Camera Video Referring to Observations from Other Vehicles Open Access

Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

The Journal of the Institute of Image Electronics Engineers of Japan Vol. 48 ( 2 ) page： 273 - 277 2019.4

Summarization of multiple news videos considering the consistency of audio-visual contents Reviewed

Ye Zhang, Ryunosuke Tanishige, Ichiro Ide, Keisuke Doman, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

International Journal of Semantic Computing Vol. 13 ( 1 ) page： 135 - 155 2019.3

Hard Negative Mining from in-Vehicle Camera Images based on Multiple Observations of Background Patterns Reviewed Open Access

Masashi Hontani, Haruya Kyutoku, David Robert Wong, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2019 Vol. 5 page： 435 - 442 2019.2

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

In recent years, the demand for highly accurate pedestrian detectors has increased due to the development of advanced driving support systems.
For the training of an accurate pedestrian detector, it is important to collect a large number of training samples.
To support this, this paper proposes a ``hard negative'' mining method to automatically extract background images which tend to be erroneously detected as pedestrians.
Negative samples are selected based on the assumption that frequent patterns observed multiple times in the same location are most likely parts of the background scene.
As a result of an evaluation using in-vehicle camera images captured along the same route, we confirmed that the proposed method can automatically collect false positive samples accurately.
We also confirmed that a highly accurate detector can be constructed using the additional negative samples.

DOI： 10.5220/0007376804350442

Open Access

Next Viewpoint Recommendation by Pose Ambiguity Minimization for Accurate Object Pose Estimation Reviewed Open Access

Nik Mohd Zarifie Hashim, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Ayako Amma, Norimasa Kobori

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2019 Vol. 5 page： 60 - 67 2019.2

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

3D object pose estimation by using a depth sensor is one of the important tasks in activities by robots. To reduce the pose ambiguity of an estimated object pose, several methods for multiple viewpoint pose estimation have been proposed. However, these methods need to select the viewpoints carefully to obtain better results. If the pose of the target object is ambiguous from the current observation, we could not decide where we should move the sensor to set as the next viewpoint. In this paper, we propose a best next viewpoint recommendation method by minimizing the pose ambiguity of the object by making use of the current pose estimation result as a latent variable. We evaluated viewpoints recommended by the proposed method and confirmed that it helps us to gain better pose estimation results than several comparative methods on a synthetic dataset.

DOI： 10.5220/0007366700600067

Open Access

Pedestrian Intensive Scanning for Active-scan LIDAR Reviewed

Taiki Yamamoto, Fumito Shinmura, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2019 Vol. 5 page： 313 - 320 2019.2

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

In recent years, LIDAR is playing an important role as a sensor for understanding environments of a vehicle’s surroundings. Active-scan LIDAR is being actively developed as a LIDAR that can control the laser irradiation direction arbitrary and rapidly. In comparison with conventional uniform-scan LIDAR (e.g. Velodyne HDL-64e), Active-scan LIDAR enables us to densely scan even distant pedestrians. In addition, if appropriately controlled, this sensor has the potential to reduce unnecessary laser irradiations towards non-target objects. Although there are some preliminary studies on pedestrian scanning strategy for Active-scan LIDARs, in the best of our knowledge, an efficient method has not been realized yet. Therefore, this paper proposes a novel pedestrian scanning method based on orientation aware pedestrian likelihood estimation using the orientation-wise pedestrian’s shape models with local distribution of measured points. To evaluate the effectiveness of the proposed method, we conducted experiments by simulating Active-scan LIDAR using point-clouds from the KITTI dataset. Experimental results showed that the proposed method outperforms conventional methods.

DOI： 10.5220/0007359903130320

Voting-based Hand-Waving Gesture Spotting from a Low-Resolution Far-Infrared Image Sequence Reviewed

Yasutomo Kawanishi, Chisato Toriyama, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomoyoshi Aizawa, Masato Kawade

Proceedings of 2018 IEEE International Conference on Visual Communications and Image Processing (VCIP2018) 2018.12

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

We propose a temporal spotting method of a hand gesture from a low-resolution far-infrared image sequence captured by a far-infrared sensor array. The sensor array captures the spatial distribution of far-infrared intensity as a thermal image by detecting far-infrared waves emitted from heat sources. It is difficult to spot a hand gesture from a sequence of thermal images captured by the sensor due to its low-resolution, heavy noise, and varying duration of the gesture. Therefore, we introduce a voting-based approach to spot the gesture with template matching-based gesture recognition. We confirm the effectiveness of the proposed temporal spotting method in several settings.

DOI： 10.1109/VCIP.2018.8698650

Gaze-inspired Learning for Estimating the Attractiveness of a Food Photo Reviewed

Akinori Sato, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

Proceedings of 20th IEEE Int. Symposium on Multimedia (ISM2018) page： 36 - 43 2018.12

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

The number of food photos posted to the Web has been increasing. Most of the users prefer to post delicious-looking food photos. They, however, do not always look delicious. A previous work proposed a method for estimating the attractiveness of food photos, that is, the degree of how much a food photo looks delicious, as an assistive technology for taking a delicious-looking food photo. This method extracted image features from the entire food photo to evaluate the impression. In our work, we conduct a preference experiment where subjects are asked to compare a pair of food photos and measure their gaze. The proposed method extracts image features from local regions selected based on the gaze information and estimates the attractiveness of a food photo by learning regression parameters. Experimental results showed the effectiveness of extracting image features from outside the gaze regions rather than inside them.

DOI： 10.1109/ISM.2018.00015

Action Recognition Using a Far-Infrared Sensor Array by Convolutional RNN Reviewed Open Access

Takayuki Kawashima, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomoyoshi Aizawa, Masato Kawade

Journal of the Japan Society for Precision Engineering Vol. 84 ( 12 ) page： 1025 - 1032 2018.12

Pedestrian Detection from a Sparse LIDAR Point-Cloud Reviewed Open Access

Yoshiki Tatebe, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

Journal of the Japan Society for Precision Engineering Vol. 84 ( 12 ) page： 1017 - 1024 2018.12

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Papers - Deguchi Daisuke