A three-level scheme for real-time ball tracking

Abstract

A three-level method is proposed to achieve robust and real-time ball tracking in soccer videos. It includes object-, intra-trajectory-, and inter-trajectory-level processing. Due to much noise and frequent occlusion, it's difficult to get the solely ball in one frame. Thus, in object level, multiple objects instead of a single one are detected and taken as ball candidates with shape and color features. Then at intra-trajectory level, each ball candidate is tracked by a Kalman filter in successive frames, which results in lots of initial trajectories in a video segment. These trajectories are thereafter scored and filtered according to their length and relationship in a time-line model. With these trajectories, we construct a distance graph, in which a node represents a trajectory, and an edge means distance between two trajectories. We use the Dijkstra algorithm to get the optimal path in the graph at the inter-trajectory level. To smooth the trajectory, we finally apply cubic spline interpolation to bridge the gap between adjacent trajectories. The algorithm is tested on broadcast soccer games in FIFA2006 and got the F-score 80.26%. The whole speed far exceeds real-time, 35.6 fps on mpeg2 data. © Springer-Verlag Berlin Heidelberg 2007.