Abstract: In order to solve the target scaling problem in visual tracking, a new adaptive multi-resolutional image tracking algorithm employing posteriori probability similarity measure is developed. The pixel-wise computational property of the posteriori probability measure is proved firstly, based on which, a maximum posteriori probability tracking algorithm is developed. The posteriori probability measure can be computed both by feature and by pixel, which enables the convenient computation of each pixel’s contribution to the similarity value. Based on this property, a new adaptive scaling method is developed. On the other hand, when the size of the tracked target becomes large, multi-resolutional skill can be employed to reduce the computation burden, which is also derived from the computation property of the employed measure. Finally, a new adaptive multi-resolutional image tracking algorithm based on posteriori probability similarity measure is constructed. Experimental results demonstrate the effectiveness of the new algorithm.