Paper Title:
Human Pose Tracking For Video Using SURF features
  Abstract

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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