Technical University of Munich

@inproceedings{hoyningen-huene_rao-blackwellized_2009,
 author = {Nvon Hoyningen-Huene and M Beetz},
 title = {Rao-Blackwellized Resampling Particle Filter for Real-Time Player
	Tracking in Sports},
 booktitle = {Fourth International Conference on Computer Vision Theory and Applications
	({VISAPP)}},
 year = {2009},
 editor = {Ranchordas, {AlpeshKumar} and Araujo, Helder},
 volume = {1},
 pages = {464--470},
 address = {Lisboa, Portugal},
 month = {feb},
 publisher = {{INSTICC} press},
 abstract = {Tracking multiple targets with similiar appearance is a common task
	in computer vision applications, especially in sports games. We propose
	a Rao-Blackwellized Resampling Particle Filter ({RBRPF)} as an implementable
	real-time continuation of a state-of-the-art multi-target tracking
	method. Target configurations are tracked by sampling associations
	and solving single-target tracking problems by Kalman filters. As
	an advantage of the new method the independence assumption between
	data associations is relaxed to increase the robustness in the sports
	domain. Smart resampling and memoization is introduced to equip the
	tracking method with real-time capabilities in the first place. The
	probabilistic framework allows for consideration of appearance models
	and the fusion of different sensors. We demonstrate its applicability
	to real world applications by tracking soccer players captured by
	multiple cameras through occlusions in real-time.},
 keywords = {soccer},
}