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IVC
2002

Towards the automatic analysis of complex human body motions

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Towards the automatic analysis of complex human body motions
The classification of human body motion is an integral component for the automatic interpretation of video sequences. In a first part we present an effective approach that uses mixed discrete/continuous states to couple perception with classification. A spline contour is used to track the outline of the person. We show that for a quasi-periodic human body motion, an autoregressive process (ARP) is a suitable model for the contour dynamics. A collection of ARP can then be used as a dynamical model for mixed state Condensation filtering, switching automatically between different motion classes. Subsequently this method is applied to automatically segment sequences which contain different motions into subsequences, which contain only one type of motion. Tracking the contour of moving people is, however, difficult. This is why we propose to classify the type of motion directly from the spatio-temporal features of the image sequence. Representing the image data as a spatio-temporal or XYT ...
Jens Rittscher, Andrew Blake, Stephen J. Roberts
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 2002
Where IVC
Authors Jens Rittscher, Andrew Blake, Stephen J. Roberts
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