Learning Robust Features for Gait Recognition by Maximum Margin Criterion
| Authors | |
|---|---|
| Year of publication | 2016 |
| Type | Article in Proceedings |
| Conference | Proceedings of the joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2016) and Statistical Techniques in Pattern Recognition (SPR 2016) |
| MU Faculty or unit | |
| Citation | BALÁŽIA, Michal and Petr SOJKA. Learning Robust Features for Gait Recognition by Maximum Margin Criterion. In Antonio Robles-Kelly, Marco Loog, Battista Biggio, Francisco Escolano, Richard Wilson. Proceedings of the joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2016) and Statistical Techniques in Pattern Recognition (SPR 2016). LNCS 10029. Switzerland: Springer International Publishing AG, 2016, p. 585-586. ISBN 978-3-319-49054-0. Available from: https://dx.doi.org/10.1007/978-3-319-49055-7. |
| web | |
| Doi | http://dx.doi.org/10.1007/978-3-319-49055-7 |
| Field | Informatics |
| Keywords | gait recognition |
| Attached files | |
| Description | Extended abstract. The full research paper "Learning Robust Features for Gait Recognition by Maximum Margin Criterion" has been accepted for publication at the 23rd IEEE/IAPR International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico, December 2016. |
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