Tracking of Multiple Moving Objects Under Outdoor Environment Using Color-based Particle Filter

Object tracking is a challenging problem due to the presence of noise, occlusion, clutter and dynamic change in the scene other than the motion of object of interest. A variety of tracking algorithms has been proposed and implemented to overcome these difficulties, but there are still some problems need to be covered. This paper proposed an algorithm to track the moving objects employing a color-based particle filter considering the single object and multiple objects in outdoor environment. We rely on Bhattacharya distance to measure the similarity between the color distribution of the target model and particles. We propose also a target-model update condition, ensuring the proper tracking object. The method is capable to track successfully the object in different outdoor environment in the presence of occlusion, clutter and dynamic change. Some experimental results and data show the feasibility and the effectiveness of our method.