Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
DE, IPSJ-DBS |
2018-12-22 10:00 |
Tokyo |
National Institute of Informatics |
An Automatic Synchronization Method of Lyrics and Pictures using Word Embedding and Generic Object Recognition Syo Yamaguchi, Daisuke Kitayama (Kogakuin Univ.) DE2018-25 |
Generating and sharing video content has become popular. Some video contents are the slideshow that combines pictures an... [more] |
DE2018-25 pp.29-34 |
SIS |
2018-12-07 10:30 |
Yamaguchi |
Hagi Civic Center |
Hardware Oriented Object Recognition Neural Network using Depth Image Yuma Yoshimoto, Hakaru Tamukoh (KIT) SIS2018-32 |
In recent years, deep learning using Convolutional Neural Network (CNN) has attracted attention as a powerful method for... [more] |
SIS2018-32 pp.55-60 |
SIS |
2017-12-14 13:50 |
Tottori |
Tottori Prefectural Center for Lifelong Learning |
Object Recognition System using Deep Learning with Depth Image for Home Service Robots Yuma Yoshimoto, Hakaru Tamukoh (Kyutech) SIS2017-55 |
In an aging society with fewer children, home service robots are expected to be realized.
In order to bring a realizati... [more] |
SIS2017-55 pp.123-128 |
PRMU, CNR |
2017-02-19 09:30 |
Hokkaido |
|
3D Generic Object Recognition based on Score Level Fusion via Superquadric Representation Ryo Hachiuma, Yuko Ozasa, Hideo Saito (Keio Univ.) PRMU2016-175 CNR2016-42 |
Our goal is to recognize 3d generic objects and estimate object's shape for object grasping simultaneously.
In this pap... [more] |
PRMU2016-175 CNR2016-42 pp.131-136 |
PRMU, IPSJ-CVIM, MVE [detail] |
2017-01-19 18:10 |
Kyoto |
|
Fish Detection and Recognition for AR-based Learning Support System in an Aquarium Chihiro Dogo (TUS), Tatsuya Kobayashi, Masaru Sugano (KDDI Research), Seiichiro Hangai (TUS) PRMU2016-139 MVE2016-30 |
This paper presents fish detection and recognition method for AR-based learning support system, which helps users to lea... [more] |
PRMU2016-139 MVE2016-30 pp.165-169 |
PRMU |
2016-10-21 16:50 |
Miyazaki |
|
Image Categorization Using Collaborative Mean Attraction Hiroki Ogihara, Masayuki Mukunoki (Univ. of Miyazaki) PRMU2016-109 |
In this paper, we apply Collaborative Mean Attraction (CMA) method, which has been applied to person re-identification p... [more] |
PRMU2016-109 pp.103-106 |
PRMU, CNR |
2015-02-20 09:00 |
Miyagi |
|
An Examination of Semantic Segmentation by Using Characteristics Information of Categories
-- by Using Object Detection, Object Recognition and Foreground-Background Information -- Shota Terui, Kazunori Kojima, Yoshiaki Itoh, Masaaki Ishigame (IPU) PRMU2014-138 CNR2014-53 |
The purpose of this study is to recognize the category of existing objects in an image per pixel. Candidate region of ob... [more] |
PRMU2014-138 CNR2014-53 pp.119-124 |
PRMU, IPSJ-CVIM, MVE [detail] |
2014-01-24 10:10 |
Osaka |
|
Object recognition by the selection of visual words according to each category using frequency histograms Tatsunori Tomura, Yasukuni Mori, Ikuo Matsuba (Chiba Univ.) PRMU2013-112 MVE2013-53 |
The general object recognition is a task that enables a computer to recognize an object and scene in images. In this pap... [more] |
PRMU2013-112 MVE2013-53 pp.195-200 |
PRMU, IPSJ-CVIM, MVE [detail] |
2014-01-24 10:40 |
Osaka |
|
* Wataru Takei, Katsuya Hosobori, Tsuyoshi Kato (Gunma Univ.), Shinichiro Omachi (Tohoku Univ.) PRMU2013-113 MVE2013-54 |
In computer vision, image crassification has been one of the central
tasks and studied by many researchers.
To deal w... [more] |
PRMU2013-113 MVE2013-54 pp.201-206 |
ITS, IE, ITE-AIT, ITE-HI, ITE-ME [detail] |
2012-02-20 16:00 |
Hokkaido |
Hokkaido Univ. |
Development of a Parking Lot Surveillance System with an Outdoor Camera Using Machine Learning Yuki Mae, Hitoshi Habe, Tomohiro Shibata (NAIST) ITS2011-44 IE2011-120 |
Currently used parking systems involve sensors, such as ultrasonic waves, infrared rays, and cameras.
These systems che... [more] |
ITS2011-44 IE2011-120 pp.165-169 |
PRMU, MVE, CQ, IPSJ-CVIM [detail] |
2012-01-19 11:10 |
Osaka |
|
Local Feature Transform with RCA and Application to general object recognition for life support Tomoki Nishimura, Haiyuan Wu, Hirokazu Taki, Hirokazu Miura (Wakayama Univ.) PRMU2011-154 MVE2011-63 |
In this paper, we propose a method for transforming local feature using relevant component analysis (RCA). Our method an... [more] |
PRMU2011-154 MVE2011-63 pp.79-84 |
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 |
PRMU, FM |
2011-12-15 11:00 |
Shizuoka |
Hamamatsu Campus, Shizuoka Univ. |
Generic Object Recognition by Graph Structural Expression Takahiro Hori, Tetsuya Takiguchi, Yasuo Ariki (Kobe Univ.) PRMU2011-127 |
This paper describes a method for generic object recognition using graph structural expression. In recent years, generic... [more] |
PRMU2011-127 pp.19-24 |
PRMU, FM |
2011-12-15 15:30 |
Shizuoka |
Hamamatsu Campus, Shizuoka Univ. |
[Special Talk]
Challenges on generic object recognition for viable products Susumu Kubota (Toshiba) PRMU2011-130 |
Currently we are working on designing products with generic object recognition capability. Since rapid prototyping is a ... [more] |
PRMU2011-130 pp.33-36 |
PRMU |
2011-02-17 10:00 |
Saitama |
|
Large Scale Image Classification using Metric based on Correlation between Multiple Image Features and Class Labels Yoshitaka Ushiku, Yuya Yamashita, Jun Imura, Hideki Nakayama, Tatsuya Harada, Yasuo Kuniyoshi (Tokyo Univ.) PRMU2010-208 |
In this paper, we propose a scalable image recognition method for both image classification and image annotation. We fir... [more] |
PRMU2010-208 pp.1-6 |
PRMU, MVE, IPSJ-CVIM [detail] |
2011-01-21 18:00 |
Shiga |
|
Video-based Generic Object Recognition by Combining Motion Features and BoF Shogo Nakamura, Daisuke Deguchi (Nagoya Univ.), Tomokazu Takahashi (Gifu Shotoku Gakuen Univ.), Ichiro Ide, Hiroshi Murase (Nagoya Univ.) PRMU2010-206 MVE2010-131 |
It has been needed to recognize objects in videos and attach tags automatically so as to categorize and search a large a... [more] |
PRMU2010-206 MVE2010-131 pp.423-428 |
IE, LOIS, ITE-ME, IEE-CMN [detail] |
2010-09-22 13:00 |
Kochi |
|
A Study on Performance Improvement of Generic Object Recognition by Object Extraction Tetsuya Fujikawa, Jiro Katto (Waseda Univ.) LOIS2010-28 IE2010-70 |
In Bag-of-Keypoints method used in generic object recognition, we ordinarily derive SIFT features over the whole regions... [more] |
LOIS2010-28 IE2010-70 pp.73-78 |
IBISML, PRMU, IPSJ-CVIM [detail] |
2010-09-05 09:30 |
Fukuoka |
Fukuoka Univ. |
Multiple Kernel Learning for Generic Object Recognition Using SIFT Gaussian Mixture Models Nakamasa Inoue, Yusuke Kamishima, Koichi Shinoda, Sadaoki Furui (Tokyo Tech) PRMU2010-58 IBISML2010-30 |
We propose a statistical framework for generic object recognition using SIFT Gaussian mixture models (GMMs) and multiple... [more] |
PRMU2010-58 IBISML2010-30 pp.7-12 |
IBISML, PRMU, IPSJ-CVIM [detail] |
2010-09-05 10:00 |
Fukuoka |
Fukuoka Univ. |
Generic Object Recognition Based on Rough Segmentation Data Given by a User Mitsuru Ambai, Yuichi Yoshida (Denso IT Laboratory, Inc.) PRMU2010-59 IBISML2010-31 |
In this paper, we revisit a generic object recognition problem from a point of view of human-computer interaction. Many ... [more] |
PRMU2010-59 IBISML2010-31 pp.13-20 |
PRMU, IE, MI |
2010-05-14 14:45 |
Aichi |
Chubu Univ. |
An Analysis of the Impact of a Training Dataset Expansion for Generic Object Recognition Takumi Toyama, Koichi Kise (Osaka Prefecture Univ.) IE2010-40 PRMU2010-28 MI2010-28 |
In the field of pattern recognition, it is well known that the contents of a training dataset affects the recognition pe... [more] |
IE2010-40 PRMU2010-28 MI2010-28 pp.145-150 |