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    Visual tracking by dictionary learning and motion estimation

    , Article 2012 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2012 ; 2012 , Pages 274-279 ; 9781467356060 (ISBN) Jourabloo, A ; Babagholami-Mohamadabadi, B ; Feghahati, A. H ; Manzuri-Shalmani, M. T ; Jamzad, M ; Sharif University of Technology
    2012
    Abstract
    In this paper, we present a new method to solve tracking problem. The proposed method combines sparse representation and motion estimation to track an object. Recently. sparse representation has gained much attention in signal processing and computer vision. Sparse representation can be used as a classifier but has high time complexity. Here, we utilize motion information in order to reduce this computation time by not calculating sparse codes for all the frames. Experimental results demonstrates that the achieved result are accurate enough and have much less computation time than using just a sparse classifier