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A new approach for multi-view gait recognition on unconstrained paths

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Author
Madrid-Cuevas, F.J.
Carmona Poyato, Ángel
Muñoz-Salinas, Rafael
Medina-Carnicer, R.
López-Fernández, D.
Date
2017
Subject
Gait recognition
Unconstrained paths
Rotation-Invariant
Angular analysis
Curved trajectories
3D reconstruction
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Abstract
Direction changes cause di culties for most of the gait recognition systems, due to appearance changes. We propose a new approach for multi-view gait recognition, which focuses on recognizing people walking on unconstrained (curved and straight) paths. To this e ect, we present a new rotation invariant gait descriptor which is based on 3D angular analysis of the movement of the subject. Our method does not require the sequence to be split into gait cycles, and is able to provide a response before processing the whole sequence. A Support Vector Machine is used for classifying, and a sliding temporal window with majority vote policy is used to reinforce the classi cation results. The proposed approach has been experimentally validated on \AVA Multi-View Dataset" and \Kyushu University 4D Gait Database" and compared with related state-of-art work. Experimental results demonstrate the e ectiveness of this approach in the problem of gait recognition on unconstrained paths
URI
http://hdl.handle.net/10396/15776
Versión del Editor
https://dx.doi.org/10.1016/j.jvcir.2016.03.020
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