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Journal of Information Science and Engineering, Vol. 24 No. 1, pp. 143-157 (January 2008)

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

Hua-Tsung Chen, Hsuan-Sheng Chen, Ming-Ho Hsiao, Wen-Jiin Tsai and Suh-Yin Lee
Department of Computer Science and Information Engineering
National Chiao Tung University
Hsinchu, 300 Taiwan

Pitching contents play the key role in the resultant victory or defeat in a baseball game. Utilizing the physical characteristic of ball motion, this paper presents a trajectory- based framework for automatic ball tracking and pitching evaluation in broadcast baseball videos. The task of ball detection and tracking in broadcast baseball videos is very challenging because in video frames, the noises may cause many ball-like objects, the ball size is small, and the ball may deform due to its high speed movement. To overcome these challenges, we first define a set of filters to prune most non-ball objects but retain the ball, even if it is deformed. In ball position prediction and trajectory extraction, we analyze the 2D distribution of ball candidates and exploit the characteristic that the ball trajectory presents in a near parabolic curve in video frames. Most of the non-qualified trajectories are pruned, which greatly improves the computational efficiency. The missed balls can also be recovered in the trajectory by applying the position prediction. The experiments of ball tracking on the testing sequences of JPB, MLB and CPBL captured from different TV channels show promising results. The ball tracking framework is able to extract the ball trajectory, superimposed on the video, and in near real-time provide visual enrichment before the next pitch coming up without specific cameras or equipments set up in the stadiums. It can also be utilized in strategy analysis and intelligence statistics for player training.

Keywords: multimedia systems, video signal process, object tracking, computer vision and image understanding, visual enrichment, sports video analysis

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Received February 2, 2007; accepted July 13, 2007.
Communicated by K. Robert Lai, Yu-Chee Tseng and Shu-Yuan Chen.
*The research is partially supported by the National Science Council of Taiwan, R.O.C., under the grant No. NSC 95-2221-E-009-076-MY3 and partially supported by Lee and MTI center for Networking Research at National Chiao Tung University.