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Event tactic analysis based on broadcast sports video

  • Guangyu Zhu
  • , Changsheng Xu
  • , Qingming Huang
  • , Yong Rui
  • , Shuqiang Jiang
  • , Wen Gao
  • , Hongxun Yao
  • School of Computer Science and Technology, Harbin Institute of Technology
  • CAS - Institute of Automation
  • China-Singapore Institute of Digital Media
  • University of Chinese Academy of Sciences
  • Microsoft USA
  • Chinese Academy of Sciences
  • Peking University

Research output: Contribution to journalArticlepeer-review

Abstract

Most existing approaches on sports video analysis have concentrated on semantic event detection. Sports professionals, however, are more interested in tactic analysis to help improve their performance. In this paper, we propose a novel approach to extract tactic information from the attack events in broadcast soccer video and present the events in a tactic mode to the coaches and sports professionals. We extract the attack events with far-view shots using the analysis and alignment of web-casting text and broadcast video. For a detected event, two tactic representations, aggregate trajectory and play region sequence, are constructed based on multi-object trajectories and field locations in the event shots. Based on the multi-object trajectories tracked in the shot, a weighted graph is constructed via the analysis of temporal-spatial interaction among the players and the ball. Using the Viterbi algorithm, the aggregate trajectory is computed based on the weighted graph. The play region sequence is obtained using the identification of the active field locations in the event based on line detection and competition network. The interactive relationship of aggregate trajectory with the information of play region and the hypothesis testing for trajectory temporal-spatial distribution are employed to discover the tactic patterns in a hierarchical coarse-to-fine framework. Extensive experiments on FIFA World Cup 2006 show that the proposed approach is highly effective.

Original languageEnglish
Article number4717216
Pages (from-to)49-67
Number of pages19
JournalIEEE Transactions on Multimedia
Volume11
Issue number1
DOIs
StatePublished - 2009
Externally publishedYes

Keywords

  • Event detection
  • object tracking
  • sports video analysis
  • tactic analysis
  • trajectory analysis

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