Track Articulated Body Motion by Pose-Model Based Stochastic Search

Articulated body motion tracking remains a challenge problem as its high-dimension and the dependence between the joint freedoms. In this paper we present a novel framework to achieve articulated body motion (walking in this paper) tracking by the use of pose-model based stochastic search algorithm which partitions the state space into two pars(pose and noise) and then processes recursively. Besides, we also use marker-based Initialization to balance the limited information of the video, use path reform to improve the overall tracking performance. Experiment demonstrates the effectiveness of our method in solving the 2D articulated human movement tracking problem.