Gait Dynamics for Recognition and Classification

dc.creator	Lee, Lily
dc.date	2004-10-08T20:36:33Z
dc.date	2004-10-08T20:36:33Z
dc.date	2001-09-01
dc.date.accessioned	2013-10-09T02:46:23Z
dc.date.available	2013-10-09T02:46:23Z
dc.date.issued	2013-10-09
dc.identifier	AIM-2001-019
dc.identifier	http://hdl.handle.net/1721.1/6657
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description	This paper describes a representation of the dynamics of human walking action for the purpose of person identification and classification by gait appearance. Our gait representation is based on simple features such as moments extracted from video silhouettes of human walking motion. We claim that our gait dynamics representation is rich enough for the task of recognition and classification. The use of our feature representation is demonstrated in the task of person recognition from video sequences of orthogonal views of people walking. We demonstrate the accuracy of recognition on gait video sequences collected over different days and times, and under varying lighting environments. In addition, preliminary results are shown on gender classification using our gait dynamics features.
dc.format	12 p.
dc.format	1128480 bytes
dc.format	92054 bytes
dc.format	application/postscript
dc.format	application/pdf
dc.language	en_US
dc.relation	AIM-2001-019
dc.subject	AI
dc.subject	gait
dc.subject	recognition
dc.subject	gender classification
dc.title	Gait Dynamics for Recognition and Classification

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