Interactive particle filter with occlusion handling for multi-target tracking

Object tracking under occlusion sense is a challenging task. Although appearance-based trackers have been greatly improved in the last decade, they are still struggling with this task. Particle filter tracking has been proven as an efficient way which could overcome nonlinear situations. Unfortunately, conventional particle filter approach encounters tracking failure during severe occlusions. In this paper, we propose an interactive particle filter method, by analyzing the occlusion relationship between different targets, the proposed algorithm select different appearance model adaptively for similarity measurement and then update the particle weight. Our method successfully resolved mutual occlusion problem in tracking multi pedestrians, experimental results show that even target is completely occluded and its trajectory is unpredictable, our algorithm is still able to achieve accurate tracking results.