Vision as Causal Activation and Association

An explicit dynamical model of vision is introduced and an optical implementation is described, represented as the spatiotemporal process of spreading activation and decaying oscillation or resonance on a fuzzy cognitive map.

Abstract

Vision is interpreted as embedding an image in a causal framework. Specifically, vision is decomposed into image recognition and image understanding. A fuzzy cognitive map (FCM)a fuzzy causal graph--is selected as the causal framework in which vision occurs. Image recognition is then interpreted as activating causal concept nodes on a FCM. Image understanding is interpreted as the causal association, via FCM edge functions, induced by recognized/activated causal nodes. Vision therefore is represented as the spatiotemporal process of spreading activation and decaying oscillation or resonance on a FCM. An explicit dynamical model of vision is introduced and an optical implementation is described.