Object Tracking Method Based on Particle Filter and Sparse Representation
YANG Da-Wei1,2,3,CONG Yang1,TANG Yan-Dong1
1.State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences, Shenyang 110016 2.University of the Chinese Academy of Sciences,Beijing 100049 3.School of Information Science and Engineering,Shenyang Ligong University,Shenyang 110159
Abstract：Aiming at the problem of illumination variation in the object tracking of video image sequence,an object tracking method which uses sparse representation in particle filter frame is proposed based on LBP textual feature of object. The tracking particles of the current frame are generated by the last tracking result according to Gaussian distribution,the sparse representation of each particle to the template subspace is obtained by solving the l1-regularized least squares problem,and the tracking object is determined. Then,particle filter is used to propagate sample distribution in next tracking frame. In the procedure,the template is updated using a new template updating strategy. The experimental results validate the performance and advancement of the proposed method.
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2013, Vol. 26 
