Motion segmentation needs to estimate the model parameters of every motion as well as its supporting region. On the basis of maximum posterior marginal probability (MPM MAP) algorithm this paper presents a new algorithm based on region shrinking to locate the supporting area. In this algorithm pixels of maximum probabilities belonging to a motion are considered to be candidate pixels for supporting region. Then the region shrinking algorithm is used to determine the region of maximum density of the candidate pixels to be the range of supporting area. Moreover

this paper presents a new approach combining the bounding box’s defining with region shrinking to estimate the initial parameters of motions. By motion dividing

motion incorporation and motion elimination the accurate number of motions can be obtained. The results of experiments show the validity of this method.