Presentation 2018-03-18
Feature extraction of object shape from motion parallax using convolutional neural network
ChengJun Shao, Makoto Murakami,
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Abstract(in English) The convolution neural networks (CNN) have good feature extraction capability. In this paper, we propose a method which can extract 3D features of object shape from a sequence of RGB images captured with a single camera through two different convolutional neural networks such as a spatial feature extraction CNN and a spatiotemporal feature extraction CNN. We extract spatial features by trained spatial feature extraction CNN, and input them to spatiotemporal feature extraction CNN and extract features of object shape. As a result of experiment using simple building blocks, we extracted motion trajectory and direction.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) convolutional neural network / motion parallax / feature extraction
Paper # BioX2017-41,PRMU2017-177
Date of Issue 2018-03-11 (BioX, PRMU)

Conference Information
Committee PRMU / BioX
Conference Date 2018/3/18(2days)
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Place (in English)
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Topics (in English)
Chair Shinichi Sato(NII) / Kazuhiko Sumi(AGU)
Vice Chair Hironobu Fujiyoshi(Chubu Univ.) / Yoshihisa Ijiri(Omron) / Hiroshi Takano(Toyama Pref. Univ.) / Hitoshi Imaoka(NEC)
Secretary Hironobu Fujiyoshi(AIST) / Yoshihisa Ijiri(NAIST) / Hiroshi Takano(Shizuoka Univ.) / Hitoshi Imaoka(Fujitsu Labs.)
Assistant Masato Ishii(NEC) / Yusuke Sugano(Osaka Univ.) / Masatsugu Ichino(Univ. of Electro-Comm.) / Naoyuki Takada(Secom) / Norihiro Okui(KDDI Research)

Paper Information
Registration To Technical Committee on Pattern Recognition and Media Understanding / Technical Committee on Biometrics
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Feature extraction of object shape from motion parallax using convolutional neural network
Sub Title (in English)
Keyword(1) convolutional neural network
Keyword(2) motion parallax
Keyword(3) feature extraction
1st Author's Name ChengJun Shao
1st Author's Affiliation Toyo University(Toyo Univ.)
2nd Author's Name Makoto Murakami
2nd Author's Affiliation Toyo University(Toyo Univ.)
Date 2018-03-18
Paper # BioX2017-41,PRMU2017-177
Volume (vol) vol.117
Number (no) BioX-513,PRMU-514
Page pp.pp.31-36(BioX), pp.31-36(PRMU),
#Pages 6
Date of Issue 2018-03-11 (BioX, PRMU)