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Recently, sparse representation has been applied to visual tracking to find the target with the minimum reconstruction error from the target template subspace. Though effective, these L1 trackers require high computational costs due to numerous calculations for 1 minimization. In addition, the inherent occlusion insensitivity of the 1 minimization has not been fully utilized. In this paper, we propose an efficient L1 tracker with minimum error bound and occlusion detection which we call Boundeddoi:10.1109/cvpr.2011.5995421 dblp:conf/cvpr/MeiLWBB11 fatcat:5vgq3jz5hngw5em25vshz7ls6a