Abstract: The normal vector at each point is estimated by finding a least square fitted plane of that point and its neighbors, and all of the estimated normal vectors are globally adjusted. Gaussian and mean curvatures at each point are estimated by quadric fitting. Eight dimensional feature vectors consisting of coordinates, normal vector, mean curvature and Gaussian curvature are taken as input feature vectors. By applying the fuzzy maximum likelihood estimate clustering method, the segmentation is implemented. Experimental results show the validity of the method.
fuzzy maximum likelihood estimate clustering,