
In this paper, a distributed multi-view object tracking algorithm is proposed to address the occlusion problem. The Bayesian sequential tracking framework is used to model the multi-view tracking problem and implemented with particle filtering. In our algorithm, the centralized computing unit is no longer needed. Image acquisition, processing and data fusion can be performed by each camera in parallel. Moreover, an adaptive observation model and an adaptive state transition model are also proposed to enable efficient data fusion and robust tracking against various occlusions. Experiments have verified the effectiveness of our algorithm.