Aiming at problem of blur caused by fast motion of target and lacking of spatial structural information usage

a tracking algorithm based on multi-task structure sparse representation is proposed. Each frame is adjusted to a fixed size in advance and the algorithm makes the most use of the whole

local and spatial structural information by the means of the overlapping patches over samples. Then

the similarity between the candidate samples and the target is determined by exploiting the alignment pooling algorithm

which can extract the coefficient information of the multi-task structure sparse representation corresponding to each image block. The experimental results on benchmark dataset show that the proposed method is more accurate and robust in dealing with fast motion and occlusion.