Saliency Based on Information Maximization

Abstract

A model of bottom-up overt attention is proposed based on the principle of maximizing information sampled from a scene. The proposed opera(cid:173) tion is based on Shannon's self-information measure and is achieved in a neural circuit, which is demonstrated as having close ties with the cir(cid:173) cuitry existent in the primate visual cortex. It is further shown that the proposed saliency measure may be extended to address issues that cur(cid:173) rently elude explanation in the domain of saliency based models. Results on natural images are compared with experimental eye tracking data re(cid:173) vealing the efficacy of the model in predicting the deployment of overt attention as compared with existing efforts.