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Robust Visual Tracking via MCMC-based Particle Filter

Abstract : 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.
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Contributor : François Septier Connect in order to contact the contributor
Submitted on : Friday, April 6, 2012 - 1:23:42 PM
Last modification on : Saturday, December 18, 2021 - 3:04:18 AM
Long-term archiving on: : Saturday, July 7, 2012 - 2:35:16 AM


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  • HAL Id : hal-00685929, version 1


D.N. Truong Cong, François Septier, Christelle Garnier, L. Khoudour, Yves Delignon. Robust Visual Tracking via MCMC-based Particle Filter. IEEE International Conference on Acoustics, Speech and Signal Processing, Mar 2012, Kyoto, Japan. ⟨hal-00685929⟩



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