3D object classification using multi-object Kohonen networks

The problem of three-dimensional planar-faced opaque object recognition from one single perspective view, is addressed in this paper. A view parameterization, based on Hough Transform, is described. Classification is accomplished by multiple multi-object Kohonen networks. A new object grouping criterion has been investigated to assign disjoint subsets of objects to each Kohonen network of the system, on the basis of input space topology. Recognition tests are presented on both synthetic and real-world 3D objects, even in the presence of partial occlusion. (C) 1996 Pattern Recognition Society. Published by Elsevier Science Ltd.