On the distribution-based tracking systems
We investigate the issues of object representation and search techniques for distribution-based tracking systems. While representing objects by color distributions has the advantage to capture the essential portion of a tracked object, it generally does not handle scale changes appropriately. We thus adopt a new object representation by integrating color and edge information via two coupled weighting schemes derived from a covariance ellipse model. The representation allows a system to perform optimization over a continuous space and to yield better tracking performances. On the aspect of search techniques, we discuss two popular iterative optimization approaches: line-search and trust-region methods. We demonstrate the differences of the two by analyzing the quality of their respective solutions through numerical and real tracking examples.