Mathias Fontmarty

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This paper presents a new algorithm for human motion three-dimensional tracking based on a stereo camera system embedded on a mobile robot. The approach mixes advantages of the well-known ICONDENSATION and annealed particle filters into a more reliable "I-Annealed" particle filter based tracker. Data fusion is also studied to show that a wide variety of(More)
Particle filters (PF) are widely used in the vision literature for visual object tracking. However, the selection and the tuning of the observation PDF (or likelihood function) involved in the particle weighting stage are often eclipsed. These considerations have a strong influence on the tracking performance, especially for human motion capture (HMC) due(More)
This paper introduces data fusion strategies within particle filtering in order to track people from a single camera mounted on a mobile robot in a human environment. Various visual cues are described, relying on color, shape or motion, together with several filtering strategies taking into account all or parts of these measurements in their importance(More)
In this article we present a two ambiance video camera system dedicated to markerless human motion capture. We introduce a new particle filter algorithm which entails an importance function enabling auto-(re)initialisation, and takes account of the global curvature of the likelihood so as to guide the search along poorly observable directions of the state(More)
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