Proceedings of the Annual Meeting of the Cognitive Science Society

Models of visual saliency normally belong to one of twocamps: models such as Experience Guided Search (E-GS),which emphasize top-down guidance based on task features,and models such as Attention as Information Maximisation(AIM), which emphasize the role of bottom-up saliency. Inthis paper, we show that E-GS and AIM are structurally simi-lar and can be unified to create a general model of visual searchwhich includes a generic prior over potential non-task relatedobjects. We demonstrate that this model displays inattentionalblindness, and that blindness can be modulated by adjustingthe relative precisions of several terms within the model. Atthe same time, our model correctly accounts for a series ofclassical visual search results.