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Gait Dynamics for Recognition and Classification

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dc.contributor.author Lee, Lily en_US
dc.date.accessioned 2004-10-08T20:36:33Z
dc.date.available 2004-10-08T20:36:33Z
dc.date.issued 2001-09-01 en_US
dc.identifier.other AIM-2001-019 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/6657
dc.description.abstract 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. en_US
dc.format.extent 12 p. en_US
dc.format.extent 1128480 bytes
dc.format.extent 92054 bytes
dc.format.mimetype application/postscript
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.relation.ispartofseries AIM-2001-019 en_US
dc.subject AI en_US
dc.subject gait en_US
dc.subject recognition en_US
dc.subject gender classification en_US
dc.title Gait Dynamics for Recognition and Classification en_US


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