Towards fast and efficient methods for tracking players in sports

An efficient algorithm for tracking a single player in a sporting match is presented in this paper. The sporting event is considered as a semi-controlled environment for which a set of closed-world assumptions regarding the visual as well as dynamical properties is derived. We show how these assumptions can be used in the context of particle filtering to arrive at a computationally-fast and reliable tracker. The proposed tracker was evaluated on a demanding data set. When compared to several similar trackers that did not utilize all of the closed-world assumptions, the proposed tracker, on average, resulted in a better performance regarding the failure rate as well as position and prediction estimation.