Robust Visual Tracking via MCMC-based Particle Filter
Résumé
We present in this paper a new visual tracking framework based on the MCMC-based particle algorithm. Firstly, in order to obtain a more informative likelihood, we propose to combine the color- based observation model with a detection confidence density ob- tained from the Histograms of Oriented Gradients (HOG) descriptor. The MCMC-based particle algorithm is then employed to estimate the posterior distribution of the target state to solve the tracking prob- lem. The global system has been tested on different real datasets. Experimental results demonstrate the robustness of the proposed sys- tem in several difficult scenarios.
Origine | Fichiers produits par l'(les) auteur(s) |
---|
Loading...