An Adaptive Vision System for Tracking Soccer Players from Variable Camera Settings (bibtex)
by Suat Gedikli, Jan Bandouch, Nico von Hoyningen-Huene, Bernhard Kirchlechner, Michael Beetz
Abstract:
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.
Reference:
Suat Gedikli, Jan Bandouch, Nico von Hoyningen-Huene, Bernhard Kirchlechner, Michael Beetz, "An Adaptive Vision System for Tracking Soccer Players from Variable Camera Settings", In Proceedings of the 5th International Conference on Computer Vision Systems (ICVS), 2007.
Bibtex Entry:
@InProceedings{gedikli07adaptive,
  author =	 {Suat Gedikli and Jan Bandouch and Nico von Hoyningen-Huene and Bernhard Kirchlechner and Michael Beetz},
  title =	{An Adaptive Vision System for Tracking Soccer Players from Variable Camera Settings},
  booktitle =	 {Proceedings of the 5th International Conference on Computer Vision Systems (ICVS)},
  year =	 {2007},
  bib2html_pubtype ={Refereed Conference Paper},
  bib2html_rescat ={Game analysis},
  bib2html_groups ={IAS, FIPM, Aspogamo},
  abstract =	 {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.}
}
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