A real-time trajectory-based ball detection-and-tracking framework for basketball video

Abstract

In a sports video, the significant events are caused mostly because of ball-player and player-player interaction. To detect and track a ball or a player in a sports video becomes more challenging in presence of many moving objects in the background. The small size of the ball in relation to the frame size makes ball detection much more difficult. In addition, the ball-images are also getting deformed due to the high speed movement of the ball. Often the ball gets occluded by players and the ball image gets merged with lines and boarders in the field. In this paper, the problem of ball detection-and-tracking in a real time basketball video is addressed. Here a trajectory based ball-detection-and-tracking method is proposed to detect and track the ball in a set of videos of basketball long shot sequences. A two-fold detection-and-tracking framework is used where the ball is detected using a feature-based method in the first step. The second step verifies the detection result of the ball detection system using the 2D-trajectory information of the possible ball candidates in the frame. The true ball trajectory is extracted from a set of candidate trajectories and the ball locations are estimated along the trajectory. The missing ball positions due to occlusion of the ball and merging of the ball image with other objects in the background are estimated using a trajectory interpolation technique.