Even though sensor fusion techniques based on particle filters have been applied to object tracking, their implementations have been limited to combining measurements from multip...
Particle filter is a sequential Monte Carlo method for object tracking in a recursive Bayesian filtering framework. The efficiency and accuracy of the particle filter depends on t...
In this work, we present some examples of applications of the so-called Rao-Blackwellised Particle Filter (RBPF). RBPFs are an extension to Particle Filters (PFs) which are applic...
Abstract--This paper presents a novel particle allocation approach to particle filtering which minimizes the total tracking distortion for a fixed number of particles over a video ...
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...