This title concerns the use of a particle filter framework to track objects defined in high-
dimensional state-spaces using high-dimensional observation spaces. Current tracking …

Particle filter (PF) is a method dedicated to posterior density estimations using weighted
samples whose elements are called particles. In particular, this approach can be applied to …

Particle Filter is an effective solution to track objects in video sequences in complex
situations. Its key idea is to estimate the density over the possible states of the object using a …

Monitoring the variables of real world dynamic systems is a difficult task due to their inherent
complexity and uncertainty. Particle Filters (PF) perform that task, yielding probability …

In this paper, we propose a novel algorithm for articulated object tracking, based on a
hierarchical search and particle swarm optimization. Our approach aims to reduce the …

Le vieillissement de la population est un enjeu majeur pour les prochaines années en
raison, notamment, de l'augmentation du nombre de personnes dépendantes. La question …

Monitoring the variables of real world dynamical systems is a difficult task due to their
inherent complexity and uncertainty. Particle Filters (PF) perform that task, yielding …

In this paper, we improve the Partitioned Sampling (PS) scheme to better handle high-
dimensional state spaces. PS can be explained in terms of conditional independences …

Je voudrais tout d'abord grandement remercier mon directeur de thèse, François Charpillet,
Directeur de recherche au centre de l'Inria Nancy, pour son encadrement, ses …

We present a markerless human motion capture system that estimates the 3D positions of
the body joints over time. The system uses a dynamic bayesian network and a factored …