A ball tracking framework for broadcast soccer video

Abstract

It is challenging to detect and track the ball from the broadcast soccer video. The feature-based tracking method to judge if a sole object is a target are inadequate because the features of the balls change fast over frames and we cannot differ the ball from other objects by them. This paper proposes a new framework to find the ball position by creating and analyzing the trajectory. The ball trajectory is obtained from the candidate collection by use of the heuristic false candidate reduction, the Kalman filter-based trajectory mining, and the trajectory evaluation. The ball trajectory is extended via a localized Kalman filter-based model matching procedure. The experimental results on two consecutive 1000-frame sequences illustrate that the proposed framework is very effective and can obtain a very high accuracy that is much better than existing methods.