CAD-based 3-D object recognition

We propose an approach to 3-D object recognition using CAD-based geometry models for freeform surfaces. Geometry is modeled with rational B-splines by defining surface patches and then combining these into a volumetric model of the object. Characteristic features are then extracted from this model and subjected to a battery of tests to select an "optimal" subset of surface features which are robust with respect to the sensor being used (e.g. laser range finder versus passive stereo) and permit recognition of the object from any viewing position. These features are then organized into a "strategy tree" which defines the order in which the features are sought, and any corroboration required to justify issuing a hypotheses. We propose the use of geometric sensor data integration techniques as a means for formally selecting surface features on free-form objects in order to build recognition strategies. Previous work has dealt with polyhedra and generalized cylinders, whereas here we propose to apply the method to more general surfaces.