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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Communication dans un congrès
ICIP 2007 - 14th IEEE International Conference on Image Processing, Sep 2007, San Antonio, Texas, United States. 1, pp.493-496, 2007, 〈10.1109/ICIP.2007.4378999〉
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https://hal.inria.fr/inria-00635937
Contributeur : Nathalie Gaudechoux <>
Soumis le : mercredi 26 octobre 2011 - 12:45:07
Dernière modification le : jeudi 11 janvier 2018 - 06:26:38

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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. 1, pp.493-496, 2007, 〈10.1109/ICIP.2007.4378999〉. 〈inria-00635937〉

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