Estimating the Number of Soccer Players using Simulation-based Occlusion Handling

Abstract

Estimating the number of soccer players is crucial in- formation for occupancy analysis and other monitoring ac- tivities in sports analysis. It depends on player detection in the field that should be independent of the environment and light conditions. Thermal cameras are therefore a bet- ter option over normal RGB cameras. Detection of non- occluded players is doable but precise estimation of number of the players in groups is hard to achieve. Here we pro- pose a novel method for estimating number of the players in groups using computer graphics and virtual simulations. Occlusion conditions are first classified by using distinctive set of features trained by a bagged tree classifier. Estima- tion of the number of players is then performed by maximum likelihood of probability density based approach to further classify the occluded players. The results show that the im- plemented strategy is capable of providing precise results even during occlusion conditions