ㆍ발행기관 : 한국인터넷정보학회ㆍ수록지정보 : KSII Transactions on Internet and Information Systems (TIIS) / 9권 / 9호 ㆍ저자명 : ( Junxing Zhang ) , ( Chunjuan Bo ) , ( Jianbo Tang ) , ( Peng Song )
In this paper, we develop a novel object tracking method based on sparse representation. First, we propose a relaxed sparse representation model, based on which the tracking problem is casted as an inverse sparse representation process. In this process, the target template is able to be sparsely approximated by all candidate samples. Second, we present an objective function that combines the sparse representation process of different fragments, the relaxed representation scheme and a weight reference prior. Based on some propositions, the proposed objective function can be solved by using an iteration algorithm. In addition, we design a tracking framework based on the proposed representation model and a simple online update manner. Finally, numerous experiments are conducted on some challenging sequences to compare our tracking method with some state-of-the-art ones. Both qualitative and quantitative results demonstrate that the proposed tracking method performs better than other competing algorithms.