Energetic Particle Filter for Online Multiple Target Tracking

Abstract : Online target tracking requires to solve two problems: data association and online dynamic estimation. Usually, association effectiveness is based on prior information and observation category. However, problems can occur for tracking quite similar targets under the constraints of missing data and complex motions. The lack in prior information limits the association performance. To remedy, we propose a novel method for data association inspired from the evolution of target's dynamic model and given by a global minimization of an energy. The concept amounts to measure the absolute geometric accuracy between features. The main advantage of our approach is that it is parameterless. We also integrate our method into the classical particle filter, that leads to what we call the energetic particle filter (EPF).
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Conference papers
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https://hal.inria.fr/inria-00635937
Contributor : Nathalie Gaudechoux <>
Submitted on : Wednesday, October 26, 2011 - 12:45:07 PM
Last modification on : Thursday, March 21, 2019 - 2:42:10 PM

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Abir El Abed, Séverine Dubuisson, Dominique Béréziat. Energetic Particle Filter for Online Multiple Target Tracking. ICIP 2007 - 14th IEEE International Conference on Image Processing, Sep 2007, San Antonio, Texas, United States. pp.493-496, ⟨10.1109/ICIP.2007.4378999⟩. ⟨inria-00635937⟩

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