A connectionist approach to multiple-view based 3-D object recognition

The authors propose a hierarchical approach to solving the surface and the vertex correspondence problems in multiple-view based 3-D object recognition systems. The proposed scheme is a coarse-to-fine search process, and a Hopfield network is employed at each stage. Compared with the conventional object matching schemes, the proposed technique provides a more general and compact formulation of the problem and a solution more suitable for parallel implementation. At the coarse search stage, the surface matching rates between the input image and each object model in the database are computed through a Hopfield network and used to select the candidates for further consideration. At the fine search stage, the object models selected from the previous stage are fed into another Hopfield network for vertex matching. The object model that has the best surface and vertex correspondences with the input image is finally singled out as the best matched model. Results of experiments using both line drawings and real range images to corroborate the proposed theory are also reported