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HMM-based gait modeling and recognition under different walking scenarios

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3 Author(s)
El-Yacoubi, M.A. ; Dept. EPH, Telecom SudParis, Evry, France ; Shaiek, A. ; Dorizzi, B.

This paper addresses gait recognition, the problem of identifying people by the way of their walk. The proposed system consists of a model-free approach which extracts features directly from the human silhouette. The dynamics of the gait are modeled using Hidden Markov Models. Experiments have been carried out on the CASIA dataset C consisting of 153 people under four walking scenarios: normal walking, slow walking, fast walking and walking while carrying a bag. The results obtained are promising and compare favorably with existing approaches.

Published in:

Multimedia Computing and Systems (ICMCS), 2011 International Conference on

Date of Conference:

7-9 April 2011

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