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In this work, we propose a robust and flexible appearance model based on the structured sparse representation framework. In our method, we model the complex nonlinear appearance manifold and occlusions as a sparse linear combination of structured union of subspaces in a basis library consisting of multiple learned low dimensional subspaces and a partitioned occlusion template set. In order to enhance...
We propose a robust visual tracker based on structured sparse representation appearance model. The appearance of tracking target is modeled as a sparse linear combination of Eigen templates plus a sparse error due to occlusions. We address the structured sparse representation that preferably matches the practical visual tracking problem by taking the contiguous spatial distribution of occlusion into...
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