Abstract. In recent years, particle filters have emerged as a useful tool that enables the application of Bayesian reasoning to problems requiring dynamic state estimation. The ef...
Particle filters encode a time-evolving probability density by maintaining a random sample from it. Level sets represent closed curves as zero crossings of functions of two variab...
Solving the tracking of an articulated structure in a reasonable time is a complex task mainly due to the high dimensionality of the problem. A new optimization method, called Sto...
Matthieu Bray, Esther Koller-Meier, Luc J. Van Goo...
To become robust, a tracking algorithm must be able to support uncertainty and ambiguity often inherently present in the data in form of occlusion and clutter. This comes usually ...
Over the last years, particle filters have been applied with great success to a variety of state estimation problems. We present a statistical approach to increasing the efficienc...