The problem of motion estimation is reviewed and a region matching 2-D motion estimation algorithm is presented. The central projection of a 3-D object moving in 3-D space is a nonrigid 2-D object which moves on the image plane. The motion of the central projection is called 2-D motion and is modeled by an affine linear transformation. If the 2-D motion is not linear or the segmentation is imperfect, this model will give a good approximation. An objective function is defined in terms of the motion parameters. The algorithm searches for that set of motion parameters which describe best the 2-D motion of the central projection. The algorithm is robust in the presence of noise and, it does not require small motion or smooth intensity profiles. It assumes that the images have been segmented. Its computation time can be significantly reduced by an appropriate choice of the initial values of the motion parameters. The performance of the algorithm is examined for different kinds of motion and various SNRs using computer generated and real images.
['Dimitrios S. Kalivas', 'Alexander A. Sawchuk']
A region matching motion estimation algorithm