This paper proposes an algorithm for tracking the ball in a soccer video sequence. Two major issues in ball tracking are 1) the image portion of the ball in a frame is very small, having blurred white color, and 2) the interaction with players causes overlapping or occlusion and makes it almost impossible to detect the ball area in a frame or consecu- tive frames. The first is solved by accumulating the image measurements in time after removing the players' blobs. The resultant image plays a role of proposal density for generating random particles in particle filter- ing. The second problem makes the ball invisible for time periods. Our tracker then finds adjacent players, marks them as potential ball hold- ers, and pursues them until a new accumulated measurement sufficient for the ball tracking comes out. The experiment shows a good perfor- mance on a pretty long soccer match sequence in spite of the ball being frequently occluded by players.
['Kyuhyoung Choi', 'Yongdeuk Seo']
Probabilistic Tracking of the Soccer Ball