Abstract: The occlusion among mobile objects during movement causes a complicated space relationship, which makes multi-view information fusion, cooperative processing and tracking difficult problem. A multi-view object tracking algorithm is proposed by combining modified fusion feature with dynamic occlusion threshold and the improved particle filter in this paper. To solve the objects characteristic uncertainty in multi-view information fusion, occlusion variable is introduced to describe space relationship among mobile objects. Through analyzing the contribution on information fusion of objects in different scene planes with the help of the positions and scales of objects, and the homography transform and sensor model, the expression of dynamic occlusion thresholds are given. After dynamically adjusting and comparing occlusion threshold, an accurate occlusion state among multiple mobile objects is obtained, which is utilized in objects characteristic fusion within common scene. Then an improved particle filter tracking algorithm based on Bayesian theory is proposed, which utilizes the modified characteristic fusion and makes the tracking system more robust to object occlusion. Experiments show that the proposed occlusion variable and dynamic occlusion threshold can effectively solve the problems of objects characteristic uncertainty and scale variation, and good tracking precision is maintained even when objects are occluded.