RECOGNITION AND POSITIONING OF PARTIALLY OCCLUDED 3-D OBJECTS

The task of recognizing and positioning the partially occluded three-dimensional (3-D) rigid objects of a given scene is considered. The surfaces of 3-D objects may be planar or curved. The 3-D surface informations are captured through range data (depth map). For recognition we use the principal curvatures, mean curvature and Gaussian curvature as the local descriptions of the surfaces. These curvatures are the local invariant features of the surfaces. A computer vision scheme, based upon the matching between the local features of the 3-D objects in a scene and those of the models which are considered as knowledge data base, is described. Finally, the hypothesis generation and verification scheme is considered for best possible recognition.