Presentation | 2017-03-20 Robust Gait Recognition for Carrying-Status by SVM-based Metric Learning using Joint Intensity Histogram Atsuyuki Suzuki, Daigo Muramatsu, Yasushi Makihara, Yasushi Yagi, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper describes a method of joint intensity metric learning to improve the robustness of gait recognition under carrying-status using gait energy image (GEI). While a silhouette-based representation such as GEI has been popular in gait recognition community due to its simple yet effective property, it is also well known that such a representation is sensitive to a change of a pedestrian’s appearance between carrying status and non-carrying status, which leads to the accuracy degradation. We therefore introduce a method of measuring dissimilarity between GEI in carrying status and GEI in non-carrying status, based on the difference of intensity co-occurence obtained from GEIs generated from same person and that from different person. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Gait recognition / Joint intensity histogram / Gait energy image (GET) / support vector machine |
Paper # | BioX2016-37,PRMU2016-200 |
Date of Issue | 2017-03-13 (BioX, PRMU) |
Conference Information | |
Committee | PRMU / BioX |
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Conference Date | 2017/3/20(2days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | |
Chair | Eisaku Maeda(NTT) / Masakatsu Nishigaki(Shizuoka Univ.) |
Vice Chair | Seiichi Uchida(Kyushu Univ.) / Hironobu Fujiyoshi(Chubu Univ.) / Akira Otsuka(AIST) / Hiroshi Takano(Toyama Pref. Univ.) |
Secretary | Seiichi Uchida(Kyoto Univ.) / Hironobu Fujiyoshi(NTT) / Akira Otsuka(NEC) / Hiroshi Takano(AIST) |
Assistant | Masaki Oonishi(AIST) / Takuya Funatomi(NAIST) / Masatsugu Ichino(Univ. of Electro-Comm.) / Naoyuki Takada(Secom) / Takahiro Aoki(Fujitsu Labs.) |
Paper Information | |
Registration To | Technical Committee on Pattern Recognition and Media Understanding / Technical Committee on Biometrics |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Robust Gait Recognition for Carrying-Status by SVM-based Metric Learning using Joint Intensity Histogram |
Sub Title (in English) | |
Keyword(1) | Gait recognition |
Keyword(2) | Joint intensity histogram |
Keyword(3) | Gait energy image (GET) |
Keyword(4) | support vector machine |
Keyword(5) | |
1st Author's Name | Atsuyuki Suzuki |
1st Author's Affiliation | Osaka University(Osaka Univ.) |
2nd Author's Name | Daigo Muramatsu |
2nd Author's Affiliation | Osaka University(Osaka Univ.) |
3rd Author's Name | Yasushi Makihara |
3rd Author's Affiliation | Osaka University(Osaka Univ.) |
4th Author's Name | Yasushi Yagi |
4th Author's Affiliation | Osaka University(Osaka Univ.) |
Date | 2017-03-20 |
Paper # | BioX2016-37,PRMU2016-200 |
Volume (vol) | vol.116 |
Number (no) | BioX-527,PRMU-528 |
Page | pp.pp.23-28(BioX), pp.23-28(PRMU), |
#Pages | 6 |
Date of Issue | 2017-03-13 (BioX, PRMU) |