Tracking people through partial occlusions

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.