ASPOGAMO: Automated SPOrt Game Analysis MOdel

The research project 'Sensor-based, Automatic Analysis of Football Games' is an ambitious, mid-term research project that studies the automation of these tasks. The main objectives of the project are (1) the investigation of novel computational mechanisms that enable computer systems to recognize intentional activities, (2) the development of an integrated software system to automate game interpretation and analysis, and (3) the demonstration of the impact of automated game analysis on application areas, such as sport science, football coaching, and sports entertainment.

For further information and videos please visit the ASpoGAMo Homepage.

Acknowledgements

This project is partly funded by the DFG under contract ASPOGAMO.

Publications

Camera-based Observation of Football Games for Analyzing Multi-agent Activities (bibtex) [pdf]
@InProceedings{Bee06camera,
  AUTHOR =	 {Michael Beetz and Jan Bandouch and Suat Gedikli and
                  Nico von Hoyningen-Huene and Bernhard Kirchlechner
                  and Alexis Maldonado},
  TITLE =	 {Camera-based Observation of Football Games for
                  Analyzing Multi-agent Activities},
  booktitle =	 {Proceedings of the Fifth International Joint
                  Conference on Autonomous Agents and Multiagent
                  Systems (AAMAS)},
  year =	 {2006},
  bib2html_pubtype ={Refereed Conference Paper},
  bib2html_rescat ={Game analysis},
  bib2html_groups ={IAS, FIPM, Aspogamo},
  bib2html_funding ={FIPM},
  bib2html_domain   = {Soccer Analysis},
  bib2html_keywords ={},
  abstract =	 {This paper describes a camera-based observation
                  system for football games that is used for the
                  automatic analysis of football games and reasoning
                  about multi-agent activity. The observation system
                  runs on video streams produced by cameras set up for
                  TV broadcasting. The observation system achieves
                  reliability and accuracy through various mechanisms
                  for adaptation, probabilistic estimation, and
                  exploiting domain constraints. It represents motions
                  compactly and segments them into classified ball
                  actions.}
}
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