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