Inattentional Blindness in Visual Search
- Matt Rounds, University of Edinburgh, Edinburgh, United Kingdom
- Chris Lucas, University of Edinburgh, Edinburgh, United Kingdom
- Frank Keller, University of Edinburgh, Edinburgh, United Kingdom
AbstractModels of visual salience normally belong to one of two camps: 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. In this paper, we show that E-GS and AIM are structurally similar and can be unified to create a general model of visual search with includes a generic prior over potential non-task related objects. We demonstrate that this model displays inattentional blindness, and that blindness can be modulated by adjusting the relative precisions of several terms within the model. At the same time, our model correctly accounts for a series of classical visual search results.
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