Combining Conspicuity Maps for hROIs Prediction

Abstract. Bottom-up cortical representations of visual conspicuity interact with top-down internal cognitive models of the external world to control eye movements, EMs, and the closely linked attention-shift mechanisms; to thus achieve visual recognition. Conspicuity operators implemented with image processing algorithms, IPAs, can discriminate human Regions-of-Interest, hROIs, the loci of eye fixations, from the rest of the visual stimulus that is not visited during the EM process. This discrimination generates predictability of the hROIs. Further, a combination of IPA-generated conspicuity maps can be used to achieve improved performance over each of the individual composing maps in terms of hROI predictions.