A hierarchical dynamic model for tracking in sports

Dynamic models play a crucial role in tracking algorithms. In particle filters, for example, proper modelling of the target dynamics can help achieving the desired tracking accuracy using only a small number of particles and thus reducing the computa- tional complexity of the tracker. We propose a novel hierarchical model for tracking players in sports by combining a conservative and a liberal dynamic model to better describe the player's dynamics. We show how parameters of the model can be estimated from prior knowledge about the players dynamics. The proposed dynamic model was compared to a widely used model and resulted in better performance in terms of estimating position and prediction.