Soccer match broadcast video analysis method based on detection and tracking

Hongyu Li, Meng Yang*, Chao Yang, Jianglang Kang, Xiang Suo, Weiliang Meng*, Zhen Li, Lijuan Mao*, Bin Sheng, Jun Qi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


We propose a comprehensive soccer match video analysis pipeline tailored for broadcast footage, which encompasses three pivotal stages: soccer field localization, player tracking, and soccer ball detection. Firstly, we introduce sports camera calibration to seamlessly map soccer field images from match videos onto a standardized two-dimensional soccer field template. This addresses the challenge of consistent analysis across video frames amid continuous camera angle changes. Secondly, given challenges such as occlusions, high-speed movements, and dynamic camera perspectives, obtaining accurate position data for players and the soccer ball is non-trivial. To mitigate this, we curate a large-scale, high-precision soccer ball detection dataset and devise a robust detection model, which achieved the (Formula presented.) of 80.9%. Additionally, we develop a high-speed, efficient, and lightweight tracking model to ensure precise player tracking. Through the integration of these modules, our pipeline focuses on real-time analysis of the current camera lens content during matches, facilitating rapid and accurate computation and analysis while offering intuitive visualizations.

Original languageEnglish
Article numbere2259
JournalComputer Animation and Virtual Worlds
Issue number3
Publication statusPublished - 1 May 2024


  • field localization
  • player tracking
  • soccer ball detection
  • video analysis
  • visualizations


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