A trajectory-based ball tracking framework with visual enrichment for broadcast baseball videos

Hua Tsung Chen*, Hsuan Sheng Chen, Ming Ho Hsiao, W. J. Tsai, Suh Yin Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Scopus citations


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.

Original languageEnglish
Pages (from-to)143-157
Number of pages15
JournalJournal of Information Science and Engineering
Issue number1
StatePublished - Jan 2008


  • Computer vision and image understanding
  • Multimedia systems
  • Object tracking
  • Sports video analysis
  • Video signal process
  • Visual enrichment


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