Scale and shape adaptive mean shift object tracking in video sequences

A new technique for object tracking based on the mean shift method is presented. Instead of using a symmetric kernel like in traditional mean shift tracking, the proposed tracking algorithm uses an asymmetric kernel which is retrieved from an object mask. During the mean shift iterations not only the new object position is located but also the kernel scale is altered according to the object scale, providing an initial adaption of the object shape. The final shape of the kernel is then obtained by segmenting the area inside and around the adapted kernel and distinguishing the object segments from the non-object segments. Thus, the object shape is tracked very well even if the object is performing out-of-plane rotations.