Robust football players tracking method for soccer scene analysis

For the analysis of soccer videos, positional information of players and ball is very essential. In order to obtain trajectories of the players, robust tracking for multiple players is highly required. In this paper, we propose a method to track multiple players in a soccer video which is captured by a single camera. In the case of capturing the video from a single view, there might be a lot of occluded situations of players. In order to overcome this problem, we propose a robust tracking method for multiple players by combining Particle Filter and Real AdaBoost Classifier. First, each target player is tracked by using Particle Filter. Next, an occluded situation is automatically detected by checking a distance between the target players. Then we resample the center of the gravities by classifier's detection after Particle Filter tracking. We show the experimental results and effectiveness of our proposed method.