A Novel Particle Filter Based Object Active Contour Tracking Method

Conventional particle filters use simple geometric shapes with finite dimensional parameters to give the tracking results, therefore cannot precisely present the real-world objects with complex shapes. Aiming at this problem, this paper presents a novel particle filter based active contour algorithm for object contour tracking task. The active contour is introduced on the base of the samples simulating the target state posterior distribution; By including the weighted particles into the energy function, the contours evolve towards the region with particles with important weights and eventually converge to image region with maximum likelihood of the target. The proposed algorithm can improve the updating accuracy of the target model and avoid the tracking drift. Finally, a real-world airport surveillance application is presented to show the effectiveness and robustness of the proposed method in complex scenarios.