Faculty Profiles - Deguchi Daisuke

Papers - Deguchi Daisuke

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Subtraction-Based General Forward Obstacle Detection from In-Vehicle Camera Images using Extended Census Transform Reviewed

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

IEEJ Transactions on Electronics, Information and Systems Vol. 136 ( 4 ) page： 588 - 589 2016.4

A classification method of cooking operations based on eye movement patterns Reviewed

Hiroya Inoue, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of Ninth Biennial ACM Symposium on Eye Tracking Research and Applications (ETRA2016) page： 205 - 208 2016.3

HandWaving Gesture Detection Using a Far-Infrared Sensor Array with Thermo-Spatial Region of Interest Reviewed

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

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2016 page： 545 - 551 2016.2

Image transformation of eye areas for synthesizing eye-contacts in video conferencing Reviewed

Takuya Inoue, Tomokazu Takahashi, Takatsugu Hirayama, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Takayuki Kurozumi, Kunio Kashino

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2016 Vol. 3 page： 273 - 279 2016.2

Human Wearable Attribute Recognition using Decomposition of Thermal Infrared Images Reviewed

Brahmastro Kresnaraman, Yasutomo Kawanishi, Daisuke Deguchi, Tomokazu Takahashi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

Proceedings of the 22th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2016) page： 123 - 127 2016.2

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

This paper addresses an attribute recognition problem in thermal images, specifically on worn objects such as hat and glasses. Although attribute recognition is a growing research field, there are not much work done in thermal infrared spectrum. In this spectrum, since illumination is not a problem, it could be a better option to be used in nighttime or poorly lit areas. The proposed method uses only the attribute information and excludes the unnecessary information for the recognition. To achieve this, we propose attribute recognition based on feature decomposition using Robust Principal Component Analysis (RPCA). An experiment to evaluate the capability of the proposed method was conducted on the dataset created for this research. The results show that the proposed method outperformed the method without decomposition by 14% in average with a maximum of 27% increase in a specific attribute.

Human Body Segmentation Using Texture Aware Grab-cut and Statistical Shape Models Reviewed

Esmaeil Pourjam, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

Proceedings of the 22th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2016) page： 28 - 33 2016.2

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

Segmentation is one of active areas in computer vision field with application in many areas from entertainment to intelligent vehicles (IVs). Among the objects, humans themselves have always been among the most interested subjects because of
their special features. Since human body has an articulated structure, modeling and recognizing different variations in the body has proved to be very difficult. Wearing various kinds of clothes in different situations which can have a completely dissimilar appearance based on the clothing type, makes the modeling much more difficult. Add to this, the common problems of vision like illumination changes, blurring due to camera movements, etc. make the problem even more difficult. Thus having a system that can segment human subjects accurately can be useful in many applications. In this paper, we propose a system for segmenting human subjects using Statistical Shapes Models (SSM) feedback and a texture aware version of Grab-cut which incorporates texture feature for improving the segmentation accuracy. Our experiments show that the proposed system has an acceptable accuracy compared to the state-of-the art interactive methods and much better than the conventional ones.

Human tracking using far-infrared sensor array (in Japanese) Reviewed

Takashi Hosono, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomoyoshi Aizawa, Masato Kawade

IEICE Transactions on Information and Systems Vol. J99-D ( 1 ) page： 119 - 129 2016.1

Prediction of driver's pedestrian detectability considering characteristics of human fields-of-view while driving (in Japanese) Reviewed

Ryunosuke Tanishige, Keisuke Doman, Daisuke Deguchi, Yoshito Mekada, Ichiro Ide, Hiroshi Murase

IEICE Transactions on Information and Systems Vol. J99-D ( 1 ) page： 56 - 66 2016.1

Position Interpolation using Feature Point Scale for Decimeter Visual Localization Reviewed

David Robert Wong, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of 2015 IEEE International Conference on Computer Vision (ICCV2015) Workshops page： 1 - 8 2015.12

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

Vehicle ego-localization is a critical task not only for in-car navigation systems, but also for emerging intelligent and autonomous vehicle technologies. Visual localization methods that determine current location by performing image matching against a pre-constructed database have an accuracy limited by the spatial distance between database images. In this paper we propose a method that uses the scale of feature points to interpolate the position of the query image between two database images. We show how this simple contribution offers an appreciable improvement in localization accuracy with an extremely minimal increase in processing time, especially when used in conjunction with image matching methods that already monitor feature scale. Our experiments showed an increase of up to 33\% in average localization accuracy when compared to a method without any interpolation.

Detector Ensemble based on False Positive Mining for Pedestrian Detection Reviewed

Yuki Suzuki, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

Proceedings of the 3rd IAPR Asian Conference on Pattern Recognition (ACPR2015) 2015.11

Generation of a video summary on a news topic based on SNS responses to news stories Reviewed

Kosuke Kato, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

Proc. 4th Int Workshop on Crowdsourcing for Multimedia (CrowdMM'15) in conjunction with ACMMM2015 page： 21 - 26 2015.10

Distant Pedestrian Re-Detection from an in-Vehicle Camera based on Detections by Other Vehicles Reviewed

Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

Proceedings of 2015 IEEE Conference on Intelligent Transportation Systems (ITSC2015) page： 1215 - 1220 2015.9

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

In this paper, we propose the re-detection paradigm, which is a detection with prior knowledge of the detection targets, and we introduce an implementation of the re-detection for distant pedestrian detection from an in-vehicle camera. We focus on the fact that other vehicles including forward vehicles can observe and detect pedestrians before the own vehicle observes them. Since appearances of pedestrians do not significantly change even though their locations are different, sharing images of the detected pedestrians among the vehicles, the own vehicle can use them as prior knowledge for detecting them again. Results of applying the proposed method to a dataset obtained by an in-vehicle camera demonstrate that the accuracy of pedestrian detection results can be significantly increased if prior knowledge of the pedestrians could be obtained.

DOI： 10.1109/ITSC.2015.200

Tastes and textures estimation of foods based on the analysis of its ingredients list and image Reviewed

Hiroki Matsunaga, Keisuke Doman, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

Vol. 9281 page： 326 - 333 2015.9

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

Recently, the number of cooking recipes on the Web is increasing.
However, it is difficult to search them by tastes or textures although
they are actually important considering the nature of the contents.
Therefore, we propose a method for estimating the tastes and the
textures of a cooking recipe by analyzing them.
Concretely, the proposed method refers to an ingredients feature from
the ``ingredients list'' and image features from the ``food image'' in
a cooking recipe.
We confirmed the effectiveness of the proposed method through an
experiment.

Statistical Shape Feedback for Human Subject Segmentation Reviewed

Esmaeil Pourjam, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

IEEJ Transactions on Electronics, Information and Systems Vol. 135-C ( 8 ) page： 1000 - 1008 2015.8

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

Human segmentation is one of the most interesting yet most challenging subjects in the field of object segmentation and image processing. It can be used in various types of applications from image retrieval to robotics and human machine interfaces, including even entertainment. Many researches have been done on this subject and it is still one of active research areas. But until now, a method for accurate segmentation in different conditions has not been introduced. In this paper, we present Statistical Shape Feedback Segmentation” (SSFSeg) method, which is a way to automatically segment human subjects (pedestrians) from single images. Our main contributions in this paper are: 1) Using human shape model as priors for Grab-cut segmentation. 2) Implementation of a feedback system which provides a coarse-to-fine way of generating more accurate shapes. For this task, we try to use masks generated by the Statistical Shape Model (SSM) algorithm as a prior input for the Grab-cut technique to segment the desired human subject in the image without user interaction. To achieve this, we propose a feedback framework for the SSM sample generation. Our experiments confirmed that the segmentation error of our proposed method is less than half of the Grab-cut method."

DOI： 10.1541/ieejeiss.135.1000

Typicality analysis of the combination of ingredients in a cooking recipe for assisting the arrangement of ingredients Reviewed

Satoshi Yokoi, Keisuke Doman, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

Proceedings of 2015 IEEE International Conference on Multimedia and Expo (ICME2012) page： 1 - 6 2015.7

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

As the number of cooking recipes posted on the Web increases, it becomes difficult to find a cooking recipe that a user needs. Moreover, even if it can be done, it is still difficult for users to arrange the cooking recipe, for example, by replacing ingredients with different ones. To deal with such problems, we propose a framework for typicality analysis of the combination of ngredients. The framework calculates a typicality value for each combination of ingredients. The list of ingredients can be arranged by adjusting the typicality value by adding or removing ingredients iteratively. The effectiveness of the proposed framework was confirmed through subjective experiments.

Pedestrian Orientation Classification Utilizing Single-Chip Coaxial RGB-ToF Camera Reviewed

Fumito Shinmura, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

Proceedings of Workshop on Environment Perception for Automated On-road Vehicles in conjunction with 2015 IEEE Intelligent Vehicles Symposium (IV2015) page： 7 - 11 2015.6

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

This paper proposes a method for pedestrian orientation classification. In image recognition, the accuracy is often degraded by the influence of background. In addition, it is also difficult to remove the background and extract only the human body from an image. To overcome these problems, we utilize a single-chip RGB-ToF camera. This camera can acquire RGB and depth images along the same optical axis at the same moment, and thus segmentation of the RGB image becomes easier by using the coaxial depth image. Our proposed method segmented a human body from its background accurately, which lead to the improvement of the accuracy of pedestrian orientation classification.

Translating Apereo Software: A Case Study using Sakai and Transifex

Yuji Tokiwa, Daisuke Deguchi, Juan Jose Merono Sanchez, Jose Mariano Lujan Gonzalez, Diego del Blanco Orobitg

2015.6

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

Web based translation support systems such as Crowdin and Transifex make it easy for regional Sakai communities to collaborate globally in translation. In the fall and winter of 2014, Spanish Sakai community and Japanese Sakai community are collaborating in translation of Sakai 10 using Transifex as a common translation platform. This collaboration brought a lot of things to two communities. For instance, to develop a tool to import resource bundle files to Transifex in a specific manner, we can have an ease of use platform to translate modular designed software such as Sakai. And this platform will be extended for every regional community and for every project in Apereo community.
During this session we will talk about followings;
(1) Overview
(2) Benefits for Apereo community
(3) Context dependent translation by gettext Portable Object
(4) Community translation strategy in Sakai Spanish Users (S2U)
(5) Automatized process by Jenkins

Multi-modal scene duplicate detection from news videos focusing on human faces Reviewed

Haruka Kumagai, Keisuke Doman, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

International Journal of Semantic Computing Vol. 9 ( 2 ) page： 215 - 237 2015.6

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

In this paper, as a tool for structuring a large volume of archived news videos according to their semantic contents, we propose a method that effectively detects scene duplicates, assuming the presence of a person speaking in the videos. A scene duplicate is defined here as a pair of video segments taken at the same event from different viewpoints. When considering scenes where a subject is speaking in news videos, referring to the audio channel could be effective to detect scene duplicates regardless of viewpoints. However, it cannot be relied on when external audio sources overlap the original one or when the subject is actually not speaking. In contrast, the image channel can be useful in most cases. However, significant difference in viewpoints could prevent accurate detection. Therefore, we propose a method that combines the results obtained from both audio and image channels in order to improve the accuracy of scene duplicate detection from news videos. The proposed method was evaluated through an experiment with actual broadcast news videos by comparing it with a conventional method. As a result, we confirmed that the detection accuracy significantly improved by the proposed method in both recall and precision.

DOI： 10.1142/S1793351X15400048

Localization of Open Source Softoware for Higher EducationCommon translation memory Reviewed

Yuji Tokiwa, Daisuke Deguchi, Makoto Miyazaki, Naoshi Hiraoka, Toshihiro Kita, Shoji Kajita

IPSJ Journal of Digital Practices Vol. 6 ( 2 ) page： 79 - 88 2015.4

Adaptive Reference Image Selection for Temporal Object Removal from Frontal In-vehicle Camera Image Sequences Reviewed

Toru Kotsuka, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2015 page： 233 - 239 2015.3

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

In recent years, image inpainting is widely used to remove undesired objects from an image. Especially, the removal of temporal objects, such as pedestrians and vehicles, in street-view databases such as Google Street View has many applications in Intelligent Transportation Systems (ITS). To remove temporal objects, Uchiyama et al. proposed a method that combined multiple image sequences captured along the same route. However, when spatial alignment inside an image group does not work well, the quality of the output image of this method is often affected. For example, large temporal objects existing in only one image create regions that do not correspond to other images in the group, and the image created from aligned images becomes distorted. One solution to this problem is to select adaptively the reference image containing only small temporal objects for spatial alignment. Therefore, this paper proposes a method to remove temporal objects by integration of multiple image sequences with an adaptive reference image selection mechanism.

DOI： 10.5220/0005357102330239

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Papers - Deguchi Daisuke