By expanding the technique of detection of a motion vector by the of time-space differential method, (1) repetitive calculations are not needed, (2) different motion vectors near the boundary of an object can be detected, and (3) coupling of the region segmentation and the framework is enabled. For this, a horizontal direction differentiating filter (104), a vertical direction differentiating filter (105), and a time direction differentiating filter (106) calculate the time-space differential ( DIFFERENTIAL I/ DIFFERENTIAL x, DIFFERENTIAL I/ DIFFERENTIAL y, DIFFERENTIAL I/ DIFFERENTIAL t) in formula (2) necessary for motion vector estimation in every pixel. A feature vector combining part (110) generates a sample vector coupling the time-space differential value and position for a random image position (x, y), and clusters from pairs of samples and classes, to minimize the difference in a maximum likelihood class determining part (112) and a maximum likelihood class data changing part (113). The motion vector is obtained from the third eigen vector of covariance matrix of the time-space differential value.
Motion vector detecting apparatus