| 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) |