Hager and Belhumeur (1998) proposed a general framework for object tracking in video images. It consists of low-order parametric models for the image motion of a target region. These models are used to predict movement and to track the target. The difference in intensity between the pixels belonging to the current region and the pixels of the selected target (learned during an offline stage) allows a straightforward prediction of the region position in the current image. The main aim of the article is to propose an important improvement within this framework, making the convergence faster with the same amount of online computation