Multiple Object Tracking for Football Game Analysis

We consider the problem of tracking football players in video captured from one side of the football field. The task is challenging due to frequent occlusions of players, varying size of players’ projections, changing illumination and similar appearance of players of the same team. We approach the problem using the tracking-by-detection paradigm, where an object detector is applied to individual video frames and the tracker tries to associate the detector responses and form the trajectories by using some motion model. We provide experiments using a classic object detector based on background modeling as well as a deep learning based detector.