MULTI-OBJECT TRACKING USING THE PARTICLE FILTER ALGORITHM ON THE TOP-VIEW PLAN

In this paper we address the problem of multi-object tracking in video sequences, with application to pedestrian tracking in a crowd. In this context, particle filters provide a robust tracking framework under ambiguity conditions. The parti-cle filter technique is used in this work, but in order to reduce its computational complexity and increase its robustness, we propose to track the moving objects by generating hypothe-ses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. 1