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Recovery of the trajectories of multiple moving objects in an image sequence with a PMHT approach

Marc Gelgon 1, 2 Patrick Bouthemy 3 Jean-Pierre Le Cadre 3
1 ATLAS - Complex data management in distributed systems
UN - Université de Nantes, Inria Rennes – Bretagne Atlantique
3 VISTA - Vision spatio-temporelle et active
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : This paper is concerned with the tracking of multiple moving objects in an image sequence and the reconstruction of the entire trajectories of these objects all over the sequence. More specifically, we address the joint issue of trajectory estimation and measurement-to-trajectory associations, which is the key problem in that context due to the occurrence of object occlusions or crossings. An original and efficient scheme is proposed, that adapts the Probabilistic Multiple Hypothesis Tracking (PMHT) technique to the case of tracking of regions in video, for which geometry and motion models can be introduced. Moreover, reliable partial associations can be obtained as an initialization. Data association and trajectory estimation are conducted within a probabilistic framework. The latter relies on Kalman filtering, while the former is solved with an EM algorithm for which a suitable initial configuration can be defined. The proposed tracking method is validated by experiments carried out on real image sequences depicting complex situations.
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Submitted on : Tuesday, March 17, 2009 - 5:51:04 PM
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Marc Gelgon, Patrick Bouthemy, Jean-Pierre Le Cadre. Recovery of the trajectories of multiple moving objects in an image sequence with a PMHT approach. Image and Vision Computing, Elsevier, 2005, 23 (1), pp.19-31. ⟨inria-00368859⟩



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