We propose an algorithm, which tracks a deformable object in complex scene based on Bayesian estimation in Particle filter framework. In Particle filter framework, both dynamic model and measure model of Particle filter, which utilizes information of structure of target edges and gray level distribution of neighbors of target edges, are respectively constructed in term of interframe correlation in the context of object tracking. The fuzzy metric is constructed to measure the similarity between histograms of template and candidate sub-regions. The tracking window can be adaptively changed with the variation of object appearance. The strategy for template update is applied according to confidence level threshold. Both judgement of occlusion and solution to occlusion are given in term of threshold and temporal window. Those experimental results illustrate that this algorithm can stably track deformable target under complex background at the low computing cost.