A novel real-time multiple objects tracking algorithm is proposed to handle the problem of occlusion in the stationary situation. Moving objects are detected using the background subtraction based on ghost detection and selective background updating model, a stable object model fusing the hue and edge features is established, and multilevel tracker queues are defined to solve the occlusion, including stable tracker queue, temporal tracker queue, lost tracker queue, and uncertain tracker queue. Then the algorithm achieves tracking multiple objects handling occlusion based on multilevel data association, and it solves the problems of new objects appearing, objects merging, and object disappearing based on different strategies. Experimental results show that our detection method could restrain ghosts and prevent the moving objects from being fused to the background. Also, the method could testify the robustness of the object model and the tracking method could effectively track the objects in the complicated situation.