Representing three-dimensional objects by sets of activities of receptive fields

Idealized models of receptive fields (RFs) can be used as building blocks for the creation of powerful distributed computation systems. The present report concentrates on investigating the utility of collections of RFs in representing three-dimensional objects under changing viewing conditions. The main requirement in this task is that the pattern of activity of RFs vary as little as possible when the object and the camera move relative to each other. I propose a method for representing objects by RF activities, based on the observation that, in the case of rotation around a fixed axis, differences of activities of RFs that are properly situated with respect to that axis remain invariant. Results of computational experiments suggest that a representation scheme based on this algorithm for the choice of stable pairs of RFs would perform consistently better than a scheme involving random sets of RFs. The proposed scheme may be useful under object or camera rotation, both for ideal lambertian objects, and for real-world objects such as human faces.