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In this paper, we propose a new visual tracking algorithm, SRAPF, for object tracking, which is based on sparse representation and annealed particle filter. To find the tracking target at a new frame, each target candidate is sparsely represented by target templates and trivial templates. The sparsity is achieved by solving a l1-regularized least squares problem. After that, Instead of tracking objects...
We propose a new Particle Filter (PF) based Particle Swarm Optimization (PSO) algorithm for 3D articulated human pose estimation. The sampling covariance and annealing factor items are incorporated into the velocity updating equation of PSO, which are initiated with appropriate values at the beginning of PSO iteration, and decreasing (`annealed') by reasonable steps. The new algorithm can, in some...
This paper proposes an annealed particle swarm optimization based particle filter algorithm for articulated 3D human body tracking. In our algorithm, a sampling covariance and an annealing factor are incorporated into the velocity updating equation of particle swarm optimization (PSO). The sampling covariance and the annealing factor are initiated with appropriate values at the beginning of the PSO...
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