Lie group approach to neural computation of image affine flow and binocular affine disparity
Thomas R. Tsao · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1995
A computational theory and neural architecture for determining image affine flow and binocular affine disparity is presented. The computation of image affine flow is formulated as a system of linear equations, and the computation of binocular affine disparity is formulated as a dynamical system defined on the parameter space of a Lie subgroup of the 2D affine Lie group. The proposed neural architecture includes a set of neurons called the Lie-germs which function as the Lie-derivative operators, a set of simple cells with dynamical receptive fields, a set of intrinsic neurons that can affine transform the receptive fields of simple cells, and an analog circuit for determining affine parameters. The result of computer simulations of the proposed neural architecture for binocular affine disparity is also presented in this paper.