BRINGING THE GRANDMOTHER BACK INTO THE PICTURE: A MEMORY-BASED VIEW OF OBJECT RECOGNITION

We describe experiments with a versatile pictorial prototype-based learning scheme for 3-D object recognition. The Generalized Radial Basis Function (GRBF) scheme seems to be amenable to realization in biophysical hardware because the only kind of computation it involves can be effectively carried out by combining receptive fields. Furthermore, the scheme is computationally attractive because it brings together the old notion of a "grandmother" cell and the rigorous approximation methods of regularization and splines.