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Tracking Multiple Objects with Particle Filtering

Carine Hue 1 Jean-Pierre Le Cadre 1 Patrick Pérez 2
1 VISTA - Vision spatio-temporelle et active
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : We address the problem of multitarget tracking encountered in many situations in signal or image processing. We consider stochastic dynamic systems detected by observation processes. The difficulty lies on the fact that the estimation of the states needs to know the assignation of the observations to the multiple targets. We propose an extension of the classical particle filter where the stochastic vector of assignation is estimated by a Gibbs sampler. This algorithm is used to estimate the trajectories of multiple targets from their noisy bearings, thus showing its ability to solve the data association problem. Moreover this algorithm can easily be extended to multireceiver observations where the receivers can produce measurements of various nature with different periodicities.
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Submitted on : Wednesday, May 24, 2006 - 10:22:52 AM
Last modification on : Friday, February 4, 2022 - 3:23:59 AM
Long-term archiving on: : Sunday, April 4, 2010 - 8:48:43 PM


  • HAL Id : inria-00072605, version 1


Carine Hue, Jean-Pierre Le Cadre, Patrick Pérez. Tracking Multiple Objects with Particle Filtering. [Research Report] RR-4033, INRIA. 2000. ⟨inria-00072605⟩



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