Optimal importance sampling for tracking in image sequences: application to point tracking

Elise Arnaud 1 Etienne Memin 1
1 VISTA - Vision spatio-temporelle et active
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : In this paper, we propose a particle filtering technique for tracking applications in image sequences. The system we propose combines a measurement equation and a dynamic equation which both depend on the image sequence. Taking into account several possible observations, the peculiar measure model we consider is a linear combination of Gaussian laws. Such a model allows us to infer an analytic expression of the optimal importance function used in the diffusion process of the particle filter. We demonstrate the significance of this model for a point tracking application. The resulting point tracker enables coping with trajectories undergoing abrupt changes, occlusion situations, large geometric deformations and noisy sequences. Its performances are shown on real world sequences.
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Communication dans un congrès
IEEE European conference on computer vision, 2004, Prague, Czech Republic. 2004
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https://hal.inria.fr/inria-00306725
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Elise Arnaud, Etienne Memin. Optimal importance sampling for tracking in image sequences: application to point tracking. IEEE European conference on computer vision, 2004, Prague, Czech Republic. 2004. 〈inria-00306725〉

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