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Importance Sampling as One Solution to the Data Association Problem in Multi-target Tracking (bibtex)
@INCOLLECTION{hoyningen-huene_importance_2010,
  author = {Hoyningen-Huene, Nicolai v and Beetz, Michael},
  title = {Importance Sampling as One Solution to the Data Association Problem
	in Multi-target Tracking},
  booktitle = {{VISIGRAPP} 2009},
  publisher = {Springer-Verlag Berlin Heidelberg},
  year = {2010},
  editor = {Ranchordas, {AlpeshKumar} and Araujo, Helder},
  number = {68},
  series = {Communications in Computer and Information Science ({CCIS)}},
  pages = {309–325},
  abstract = {Tracking multiple targets with similar appearance is a common task
	in many computer vision applications as surveillance or sports analysis.
	We propose a Rao-Blackwellized Resampling Particle Filter ({RBRPF)}
	as a real-time multi-target tracking method that solves the data
	association problem by a Monte Carlo approach. Each particle containing
	the whole target configuration is predicted by using a process model
	and resampled by sampling associations and fusing of the predicted
	state with the assigned measurement(s) instead of the common dispersion.
	As each target state is modeled as a Gaussian, Rao-Blackwellization
	can be used to solve some of these steps analytically. The sampling
	of associations splits the multi-target tracking problem in multiple
	single target tracking problems, which can be handled by Kalman filters
	in an optimal way. The method is independent of the order of measurements
	which is mostly predetermined by the measuring process in contrast
	to other state-of-the-art approaches. Smart resampling and memoization
	is introduced to equip the tracking method with real-time capabilities
	in the first place exploiting the discreteness of the associations.
	The probabilistic framework allows for consideration of appearance
	models and the fusion of different sensors. A way to constrain the
	multiplicity of measurements associated with a single target is proposed
	and – along with the ability to cope with a high number of targets
	in clutter – evaluated in a simulation experiment. We demonstrate
	the applicability of the proposed method to real world applications
	by tracking soccer players captured by multiple cameras through occlusions
	in real-time.}
}
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Last edited 29.01.2013 17:37 by Quirin Lohr