Gait Dynamics for Recognition and Classification

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6657

Full metadata record

DC Field	Value	Language
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	-
Appears in Collections:	MIT Items

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