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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,...
Using particle filter to track human movement, a key problem is how to draw samples in high-dimensional state space. In this paper, we present a novel framework of particle filtering, namely Hierarchical Genetic Particle Filter (HGPF), to improve the efficiency of samples by a hierarchical evolutionary detection. As a result, we can obtain reasonably distributed samples thus translating into reliable...
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