Robust Visual Tracking Using Particle Filtering on SL(3) Group

Abstract:

Considering the process of objects imaging in the camera is essentially the projection transformation process. The paper proposes a novel visual tracking method using particle filtering on SL(3) group to predict the changes of the target area boundaries of next moment, which is used for dynamic model. Meanwhile, covariance matrices are applied for observation model. Extensive experiments prove that the proposed method can realize stable and accurate tracking for object with significant geometric deformation, even for nonrigid objects.

• Periodical: Applied Mechanics and Materials (Volumes 457-458)
• Pages: 1028-1031
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.457-458.1028
• Online since: October 2013
• Authors: Ying Hong Xie*, Cheng Dong Wu
• Keywords: Particle Filtering, Riemannian Manifold, SL(3) Group, Visula Tracking

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