Technical University of Munich

@article{beetz_aspogamo:_2009,
 author = {M Beetz and Nvon Hoyningen-Huene and B Kirchlechner and S Gedikli and F Siles and Mand LM Durus},
 title = {{ASpoGAMo:} Automated Sports Game Analysis Models},
 journal = {International Journal of Computer Science in Sport},
 year = {2009},
 volume = {8},
 number = {1},
 abstract = {We propose automated sport game models as a novel technical means
	for the analysis of team sport games. The basic idea is that automated
	sport game models are based on a conceptualization of key notions
	in such games and probabilistically derived from a set of previous
	games. In contrast to existing approaches, automated sport game models
	provide an analysis that is sensitive to their context and go beyond
	simple statistical aggregations allowing objective, transparent and
	meaningful concept definitions. Based on automatically gathered spatio-temporal
	data by a computer vision system, a model hierarchy is built bottom
	up, where context-sensitive concepts are instantiated by the application
	of machine learning techniques. We describe the current state of
	implementation of the {ASpoGaMo} system including its computer vision
	subsystem that realizes the idea of automated sport game models.
	Their usage is exemplified with an analysis of the final of the soccer
	World Cup 2006.},
 keywords = {soccer},
}