Classic Mean shift based tracking algorithm uses fixed kernel-bandwidth
which limits the performance when the object scale exceeds the size of the tracking window. Although some modified algorithms can settle the problem of object zooming in a way
these algorithms are helpless to the object rotation. Based on the analysis of the scale-space theory and the current Mean shift algorithms
a scale and direction adaptive mean shift tracking algorithm is proposed. Experimental results show that the new method can effectively and accurately obtain the best description of the target areas for the first frame
and the new mean shift tracking algorithm can adapt to any kind of object’s movements.