A GPU-accelerated Particle Filter with Pixel-level Likelihood
Claus Lenz, Giorgio Panin, Alois Knoll · 2008
We present in this paper a GPU-accelerated par-ticle filter based on pixel-level segmentation and matching, for real-time object tracking. The pro-posed method achieves real-time perfomance, while computing for each particle the corresponding filled model silhouette through the rendering engine of the graphics card, and comparing it with the un-derlying binary map of the segmentation prepro-cess. With the proposed approach, a better precision and generality is obtained with respect to related feature-level likelihoods such as color histograms, while keeping low computational requirements. 1