This article presents a novel people-tracking approach to cope with partial occlusions caused by scene objects. Instead of predicting when and where the occlusions will occur, a part-based model is used to model the p...This article presents a novel people-tracking approach to cope with partial occlusions caused by scene objects. Instead of predicting when and where the occlusions will occur, a part-based model is used to model the pixel distribution of the target body under occlusion. The subdivided patches corresponding to a template image will be tracked independently using Markov chain Monte Carlo （MCMC） method. A set of voting-based rules is established for the patch-tracking result to verify if the target is indeed located at the estimated position. Experiments show the effectiveness of the proposed method.展开更多
基金supported by the National Natural Science Foundation of China(60772114)
文摘This article presents a novel people-tracking approach to cope with partial occlusions caused by scene objects. Instead of predicting when and where the occlusions will occur, a part-based model is used to model the pixel distribution of the target body under occlusion. The subdivided patches corresponding to a template image will be tracked independently using Markov chain Monte Carlo （MCMC） method. A set of voting-based rules is established for the patch-tracking result to verify if the target is indeed located at the estimated position. Experiments show the effectiveness of the proposed method.
