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Communication Dans Un Congrès Année : 2011

HMM-based gait modeling and recognition under different walking scenarios

Résumé

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
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Dates et versions

hal-01302472 , version 1 (14-04-2016)

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Mounim El Yacoubi, Ayet Shaiek, Bernadette Dorizzi. HMM-based gait modeling and recognition under different walking scenarios. ICMCS 2011 : 2nd International Conference on Multimedia Computing and Systems, Apr 2011, Ouarzazate Morocco. pp.1 - 5, ⟨10.1109/ICMCS.2011.5945573⟩. ⟨hal-01302472⟩
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