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Vision as Causal Activation and Association

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.