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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IE, IMQ, MVE, CQ (Joint) [detail] |
2020-03-05 13:50 |
Fukuoka | Kyushu Institute of Technology (Cancelled but technical report was issued) |
 IMQ2019-21 IE2019-103 MVE2019-42 |
(To be available after the conference date) [more] | IMQ2019-21 IE2019-103 MVE2019-42 pp.31-34 |
| EMM, IT | 2019-05-23 14:00 |
Hokkaido | Asahikawa International Conference Hall | Generation of privacy-preserving images holding positional information for HOG feature extraction Masaki Kitayama, Hitoshi Kiya (Tokyo Metro. Univ.) IT2019-1 EMM2019-1 |
In this paper, we propose a generation method of images which have no visual information but hold the gradient direction... [more] | IT2019-1 EMM2019-1 pp.1-6 |
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 13:40 |
Okinawa | MI2017-79 |
(To be available after the conference date) [more] | MI2017-79 pp.45-46 |
|
| PRMU, IPSJ-CVIM, MVE [detail] | 2017-01-20 15:35 |
Kyoto | Cooking Gesture Recognition based on Spatio-Temporal Histogram of Oriented Gradient Features Seiji Kojima, Wataru Ohyama, Tetsushi Wakabayashi (Mie Univ.) PRMU2016-145 MVE2016-36 |
In this research, we propose a cooking gesture recognition method． The outline of this research is as follows， (1) Act... [more] |
PRMU2016-145 MVE2016-36 pp.315-319 |
|
| IE, ITE-ME, IPSJ-AVM, ITE-CE [detail] | 2016-08-08 14:30 |
Fukuoka | Sugimoto Yudai, Sagara Kazutaka, Zhang Lifeng (Kyutech) IE2016-49 |
This study is proposed on detection of Echizen Jellyfish from an image which was uploaded to the internet. The outbreak ... [more] | IE2016-49 pp.23-26 |
|
| RECONF | 2015-09-18 09:50 |
Ehime | Ehime University | Comparison of machine learning classifiers for HOG-based human detection on an FPGA Masahito Oishi, Yoshiki Hayashida, Ryo Fujita, Yuichiro Shibata, Kiyoshi Oguri (Nagasaki Univ.) RECONF2015-34 |
In this paper, we compare Real AdaBoost and a linear SVM from a view point of FPGA implementation of an image-based huma... [more] | RECONF2015-34 pp.13-18 |
| VLD, DC, IPSJ-SLDM, CPSY, RECONF, ICD, CPM (Joint) [detail] |
2014-11-26 11:35 |
Oita | B-ConPlaza | Efficient FPGA resource allocation for HOG-based human detection Masahito Oishi, Yuichiro Shibata, Kiyoshi Oguri (Nagasaki Univ.) RECONF2014-39 |
In this paper, we discuss implementation for highly efficient and compact FPGA implementation of an image-based real-ti... [more] |
RECONF2014-39 pp.31-36 |
| ICD | 2012-12-17 15:55 |
Tokyo | Tokyo Tech Front | [Poster Presentation]
FPGA Implementation of HOG-based Real-Time Object Detection Processor Kenta Takagi, Kosuke Mizuno, Shintaro Izumi, Hiroshi Kawaguchi, Masahiko Yoshimoto (Kobe Univ.) ICD2012-105 |
Histogram of Oriented Gradients (HOG) is widely accepted feature descriptor for object detection. HOG is robust against ... [more] | ICD2012-105 p.61 |
| PRMU, FM | 2011-12-15 09:30 |
Shizuoka | Hamamatsu Campus, Shizuoka Univ. | A study on spatio-temporal CoHOG features for recognition of generic objects in video Shogo Nakamura, Daisuke Deguchi (Nagoya Univ.), Tomokazu Takahashi (Gifu Shotoku Gakuen Univ.), Ichiro Ide, Hiroshi Murase (Nagoya Univ.) PRMU2011-124 |
Recognizing objects in videos is one of the important technologies to search a large amount of videos efficiently on the... [more] | PRMU2011-124 pp.1-6 |
| RECONF, VLD, CPSY, IPSJ-SLDM [detail] | 2011-01-18 09:40 |
Kanagawa | Keio Univ (Hiyoshi Campus) | FPGA implementation of human detectin with HOG features and AdaBoost Kazuhiro Negi, Keisuke Dohi, Yuichiro Shibata, Kiyoshi Oguri (Nagasaki Univ.) VLD2010-100 CPSY2010-55 RECONF2010-69 |
An increase in in-home accidental deaths of elderly person caused by falling and fainting, which are nonfatal if detect... [more] |
VLD2010-100 CPSY2010-55 RECONF2010-69 pp.117-122 |
| HIP, HCS | 2010-05-14 15:20 |
Okinawa | Okinawa Industry Support Center | Generic Object Recognition with multiple Local features for Information Presentation system Satoru Odo (Okinawa Univ.) HCS2010-22 HIP2010-22 |
This is to propose the information display system aimed at applications to the welfare field such as memory compensation... [more] | HCS2010-22 HIP2010-22 pp.121-123 |
| PRMU, HIP | 2010-03-16 15:05 |
Kagoshima | Kagoshima Univ. | Hand Shape Recognition based on SVM and online learning with HOG Ryousuke Mutou, Kazutaka Shimada, Tsutomu Endo (Kyushu Inst. of Tech.) PRMU2009-311 HIP2009-196 |
In this paper, we proposed a combined method for hand shape recognition. It consists of support vector machines (SVMs) a... [more] | PRMU2009-311 HIP2009-196 pp.459-464 |
| ITE-AIT, IE, ITE-HI, ITE-ME, ITS | 2010-02-16 16:15 |
Hokkaido | Graduate School of Information and Technology, Hokkaido Univ. | Vehicle Tracking Using Deformable Model and Particle Filter Akihiro Takeuchi, Seiichi Mita (Toyota Technological Inst.) ITS2009-84 IE2009-178 |
In this paper, we propose the method for vehicle detection and tracking using vehicle mounted cameras. Our method learns... [more] | ITS2009-84 IE2009-178 pp.269-274 |
| MI | 2010-01-28 17:40 |
Okinawa | Naha-Bunka-Tenbusu | Endoscopic image matching for reconstructing 3-D structure of intestine Katsuhiro Hirai, Yasushi Kanazawa (Toyohashi Univ. of Tech.), Ryusuke Sagawa, Yasushi Yagi (Osaka Univ.) MI2009-117 |
We present an image matching method between endoscopic images for reconstructing 3-D shape of an intestine. In this cas... [more] | MI2009-117 pp.223-228 |
| SIS | 2009-06-11 14:40 |
Okinawa | Hardware Implementation of HOG feature Extraction for Real-time Pedestrian Recognition Ryoji Kadota (Kyoto Univ.), Yukihiro Nakamura (Ritsumeikan Univ.), Ryusuke Miyamoto (Nara Inst. of Sci and Tech.) SIS2009-8 |
Pedestrian recognition is one of the most challenging problems in the field of computer vision. In this study, fea... [more] |
SIS2009-8 pp.43-48 |
|
| ITS, IEE-ITS | 2009-03-09 14:50 |
Kyoto | Kyoto University | Road Sign Recognition with Color and Edge based features Sho Shimamura, Satoshi Yonemoto (Kyushu Sangyo Univ.) ITS2008-87 |
This paper presents a new road sign recognition method with color and edge based features. First, extraction of color re... [more] | ITS2008-87 pp.23-28 |
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