A Trajectory-Based Ball Tracking Framework with Enrichment for Broadcast Baseball Videos

Abstract

For ball detection and trajectory extraction in broadcast baseball videos, this paper presents a novel framework which utilizes motion characteristic to extract ball trajectory from lots of moving objects. First, a series of constraints are applied to reduce ball candidates in each frame. Analyzing the distribution of ball candidates, the estimate function is built to explore the trajectory for the pitched ball. The experiments of ball tracking on broadcast baseball videos of JPB, MLB and CPBL from different channels show promising results. In addition, for video enrichment, the obtained baseball trajectory is superimposed on the frame to present the pitch in detail, which not only provides entertainment effects but also can be applied to baseball player training.