Segmentation and 2D motion estimation by region fragments

In estimating multiple image motions, a central problem is that 2D motion estimation and region segmentation are mutually dependent. This paper presents a new region description method for dealing with this mutual dependence problem. Segmentation and motion esiimation are simultaneously performed by a clustering process based on color, motion, and pixel position. As a result of the clustering, an image is decomposed into region fmgments. Each fmgment is characterized by distribution parameters of color, pixel positions, and spatiotemporal intensity gradients. The image is described by the parameters of the region fragments. 2D motion vectors for each fragment are obtained from the distribution parameters of the intensity gradients. By combining those features in the clustering process, regions are segmented more precisely, motion boundaries are not blurred, and the 2D motions are obtained even in noisy areas. Experimental results of this new method are shown in this paper.