Recognizing tactic patterns in broadcast basketball video using player trajectory

Hua-Tsung Chen*, Chien Li Chou, Tsung Sheng Fu, Suh-Yin Lee, Bao-Shuh Lin 

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


The explosive growth of the sports fandom inspires much research on manifold sports video analyses and applications. The audience, sports fans, and even professionals require more than traditional highlight extraction or semantic summarization. Computer-assisted sports tactic analysis is inevitably in urging demand. Recognizing tactic patterns in broadcast basketball video is a challenging task due to its complicated scenes, varied camera motion, frequently occlusions between players, etc. In basketball games, the action screen means that an offensive player perform a blocking move via standing beside or behind a defender for freeing a teammate to shoot, to receive a pass, or to drive in for scoring. In this paper, we propose a screen-strategy recognition system capable of detecting and classifying screen patterns in basketball video. The proposed system automatically detects the court lines for camera calibration, tracks players, and discriminates the offensive/defensive team. Player trajectories are calibrated to the real-world court model for screen pattern recognition. Our experiments on broadcast basketball videos show promising results. Furthermore, the extracted player trajectories and the recognized screen patterns visualized on a court model indeed assist the coach/players or the fans in comprehending the tactics executed in basketball games informatively and efficiently.

Original languageEnglish
Pages (from-to)932-947
Number of pages16
JournalJournal of Visual Communication and Image Representation
Issue number6
StatePublished - 1 Aug 2012


  • Broadcast basketball video
  • Camera calibration
  • Kalman filter
  • Multimedia system
  • Object tracking
  • Pattern recognition
  • Sports video analysis
  • Tactic analysis

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