A improved silhouette tracking approach integrating particle filter with graph cuts
In this paper, we propose a novel approach that combines particle filter tracking and 3D graph cut based segmentation to achieve silhouette tracking against drastic scale change and occlusion. The segmentation module offers particle filter tracking procedure the target shape information to compensate spatial information loss in the histogram based particle filter tracking process. Meanwhile, particle filter predicts a location for the shape prior in the segmentation module to overcome the global nature of graph cut algorithm, that is outlying regions similar with object are prone to be captured. The above two parts are linked with a guide mask that is initialized at the beginning of tracking and updated in a mask update mechanism. We demonstrate the effectiveness of our approach with experiments in several challenging image sequences.