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Visual tracking via adaptive structural local sparse appearance model
2012
2012 IEEE Conference on Computer Vision and Pattern Recognition
Sparse representation has been applied to visual tracking by finding the best candidate with minimal reconstruction error using target templates. However most sparse representation based trackers only consider the holistic representation and do not make full use of the sparse coefficients to discriminate between the target and the background, and hence may fail with more possibility when there is similar object or occlusion in the scene. In this paper we develop a simple yet robust tracking
doi:10.1109/cvpr.2012.6247880
dblp:conf/cvpr/JiaLY12
fatcat:4vzbrlsygnhives5kuervlwvte