Multi-view gait recognition on curved
Autor
López-Fernández, D.
Madrid-Cuevas, F.J.
Carmona Poyato, Ángel
Muñoz-Salinas, Rafael
Medina-Carnicer, R.
Fecha
2017-12-11Materia
Gait recognition3D descriptor
Independent-view
Curved paths
METS:
Mostrar el registro METSPREMIS:
Mostrar el registro PREMISMetadatos
Mostrar el registro completo del ítemResumen
Appearance changes due to viewing angle changes cause difficulties for most of the gait recognition methods. In this paper, we propose a new approach for multi-view recognition, which allows to recognize people walking on curved paths. The recognition is based on 3D angular analysis of the movement of the walking human. A coarse-to-fine gait signature represents local variations on the angular measurements along time. A Support Vector Machine is used for classifying, and a sliding temporal window for majority vote policy is used to smooth and reinforce the classification results. The proposed approach has been experimentally validated on the publicly available “Kyushu University 4D Gait Database”.