A survey on soccer player detection and tracking with videos

Soccer is a popular sport, and there is a growing need for automated analysis of soccer videos, while the detection and tracking of the players is the indispensable prerequisite. In this paper, we first introduce and classify multi-object tracking and then present two mostly used multi-object tracking methods, DeepSort and TrackFormer. When multi-object tracking is applied to soccer scenarios, some preprocessing and post-processing are generally performed, with preprocessing including processing of the video, such as splicing and background removing, and post-processing including further applications, such as player mapping for a 2D stadium. By directly employing the two methods above, we test the real scene and train TrackFormer to get further results. Meanwhile, in order to facilitate researchers who are interested in multi-object tracking as well as in the direction of player tracking, recent advances in preprocessing and processing methods for soccer player tracking are given and future research directions are suggested.