Fragment-based visual tracking with adaptive appearance model - ZHAO Ling; FENG Bin; QIU Jin-bo (Tongxin xuebao, 2011)
A joint object was proposed which combine the target and the occluder in order to exploit the characteristics of the occluder to evolve the target template.To this end,the Gaussians mixture model（GMM） was introduced to enable an adaptive learning mechanism.Each pixel of the template is modeled using a GMM with three components.Once the template-matching is achieved in the current frame,the pixel value is used to update a specific component in its GMM.After that,the pixel will also be updated.Experimental results show that the proposed method is robust with respect to the partial occlusions and natural appearance changes.