A robust algorithm for tracking object under occlusion and illumination change
Hong Lu, Hongsheng Li, Wenlin Zou, Shumin Fei · 2012
An adaptive threshold value (ATV) and two-orthogonal-orientation edge correlogram (TOEC) based algorithm is proposed for tracking moving object in real scenarios. The ATV is used to extract the object edges under illumination changes. To improve the object edges representation power, the TOEC encodes the edge orientation pair levels along two orthogonal directions explicitly. An entropy weighting-maximization scheme is presented to achieve the maximum likelihood estimation of the similar regions and scales. Experimental results show that the proposed approach is appealing with respect to the robustness in the scenarios of complex occlusions and illumination variations.