Human Pose Tracking For Video Using SURF features

Abstract:

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In this paper, a novel method based on SURF features method for tracking human motion in monocular videos is proposed. With a initial human skeleton joint point template, we use the probability density propagation of the particle filers through the model. This algorithm can automatically achieve right human motion figure from tracking failures, such as occlusion and auto-occlusion problem. Experimental results from 20 classes monocular videos show that the new Based on SURF method is robust and the tracking results are good.

Info:

Periodical:

Edited by:

Yuanzhi Wang

Pages:

203-209

DOI:

10.4028/www.scientific.net/AMM.39.203

Citation:

O. Y. Yi "Human Pose Tracking For Video Using SURF features", Applied Mechanics and Materials, Vol. 39, pp. 203-209, 2011

Online since:

November 2010

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Price:

$35.00

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