Generation of Ball Possession Statistics in Soccer Using Minimum-Cost Flow Network

Saikat Sarkar, Amlan Chakrabarti, Dipti Prasad Mukherjee; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2019, pp. 0-0

We present an automatic technique for calculating ball possession statistics from the video of a soccer match. The possession statistics is generated based on the number of valid passes made by an individual team. A valid pass is detected as a split or merge event of the ball with a player. A pass starts when the ball splits from a player. A pass ends when the ball merges with a player. We use a minimum-cost flow network to model number of valid passes in the soccer match. The ball and the players represent the nodes of the network. Each edge of the network is associated with a cost derived from the between-frame correspondences of the ball and the players. The total flow through the network is optimized to track the number of valid passes. Experimental results show that the accuracy of the proposed method is at least 4% better than that of a similar approach.