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Rao-Blackwellized Resampling Particle Filter for Real-Time Player Tracking in Sports (bibtex)
Rao-Blackwellized Resampling Particle Filter for Real-Time Player Tracking in Sports (bibtex)
by Nvon Hoyningen-Huene and M Beetz
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.
Reference:
Rao-Blackwellized Resampling Particle Filter for Real-Time Player Tracking in Sports (Nvon Hoyningen-Huene and M Beetz), In Fourth International Conference on Computer Vision Theory and Applications (VISAPP) (A Ranchordas, H Araujo, eds.), INSTICC press, volume 1, 2009. 
Bibtex Entry:
@inproceedings{hoyninge09visapp,
 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},
 pages = {464-470},
 editor = {AlpeshKumar Ranchordas and Helder Araujo},
 volume = {1},
 address = {Lisboa, Portugal},
 month = {Feb.},
 organization = {INSTICC},
 publisher = {INSTICC press},
 bib2html_pubtype = {Refereed Conference Paper},
 bib2html_rescat = {Perception},
 bib2html_groups = {Aspogamo},
 bib2html_funding = {ASpoGAMo},
 bib2html_domain = {Soccer Analysis},
 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.
  },
}
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