An Adaptive Vision System for Tracking Soccer Players from Various Camera Settings


  • Suat Gedikli
  • Jan Bandouch
  • Nico von Hoyningen-Huene
  • Bernhard Kirchlechner
  • Michael Beetz



video analysis, state estimation, object recognition, object tracking, sport games, DDC: 004 (Data processing, computer science, computer systems)


In this paper we present Aspogamo, a vision system capable of estimating motion trajectories of soccer players taped on video. The system performs well in a multitude of application scenarios because of its adaptivity to various camera setups, such as single or multiple camera settings, static or dynamic ones. Furthermore, Aspogamo can directly process image streams taken from TV broadcast, and extract all valuable information despite scene interruptions and cuts between different cameras. The system achieves a high level of robustness through the use of modelbased vision algorithms for camera estimation and player recognition and a probabilistic multi-player tracking framework capable of dealing with occlusion situations typical in team-sports. The continuous interplay between these submodules is adding to both the reliability and the efficiency of the overall system.






The 5th International Conference on Computer Vision Systems