| Presentation | 2018-12-25 Human Gait Recognition Method for Long and Baggy Clothes Using Machine Learning Abrar Alharbi, Eiji Kamioka, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Human gait is a significant biometric feature used for the identification of people by their style of walking. In comparison with other methods of biometric information, gait offers recognition from a distance at low resolution while requiring no user interaction, whereas other biometrics are likely to require a certain level of interaction. In This paper, a human gait recognition method is presented to identify people who are wearing long baggy clothes like Thoub and Abaya. Microsoft Kinect sensor is used as a tool to establish a skeleton based gait database. The skeleton joint positions are obtained and used as input parameters for classification. An evaluation experiment was carried out with 15 walking subjects, each having 30 walking sequences in total, achieving the recognition rate of 100% using Support Vector Machine classifier. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Gait Recognition / Biometric Systems / Kinect Sensor / Model-based System / Machine Learning |
| Paper # | MoNA2018-50 |
| Date of Issue | 2018-12-18 (MoNA) |
| Conference Information | |
| Committee | MoNA |
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| Conference Date | 2018/12/25(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | General |
| Chair | Ryoichi Shinkuma(Kyoto Univ.) |
| Vice Chair | Shigeaki Tagashira(Kansai Univ.) / Gen Kitagata(Tohoku Univ.) |
| Secretary | Shigeaki Tagashira(Kyushu Univ.) / Gen Kitagata(NEC) |
| Assistant | Ken Usui(KDDI Research) / Kenji Kanai(Waseda Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Mobile Network and Applications |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Human Gait Recognition Method for Long and Baggy Clothes Using Machine Learning |
| Sub Title (in English) | |
| Keyword(1) | Gait Recognition |
| Keyword(2) | Biometric Systems |
| Keyword(3) | Kinect Sensor |
| Keyword(4) | Model-based System |
| Keyword(5) | Machine Learning |
| 1st Author's Name | Abrar Alharbi |
| 1st Author's Affiliation | Shibaura Institute of Technology(SIT) |
| 2nd Author's Name | Eiji Kamioka |
| 2nd Author's Affiliation | Shibaura Institute of Technology(SIT) |
| Date | 2018-12-25 |
| Paper # | MoNA2018-50 |
| Volume (vol) | vol.118 |
| Number (no) | MoNA-378 |
| Page | pp.pp.67-72(MoNA), |
| #Pages | 6 |
| Date of Issue | 2018-12-18 (MoNA) |