SSD tracking using dynamic template and log-polar transformation

With the assumption of small motion displacements in sequences, templates can be matched successfully by SSD (sum-squared-difference) optimization technique. In this paper two crucial modifications are proposed to improve the original SSD tracking. First, templates are dynamically updated for each frame. Thus, instead of designing complicated parametric models to explain various image distortions in tracking sequences, more efficient and compact parametric models, say the pure translation model, can be adopted. Second, rotation and scale can be incorporated into a translation motion model after a log-polar transformation. Extensive experimental results performed on live video sequences show the effectiveness and advantage of our approach.