Keywords
attention, vision, eye movements, conspicuity, saliency
Abstract
Building on our presentation at MODVIS 2015, we continue in our quest to discover a functional, computational, explanation of the relationship among visual attention, interpretation of visual stimuli, and eye movements, and how these produce visual behavior. Here, we focus on one component, how selection is accomplished for the next fixation. The popularity of saliency map models drives the inference that this is solved; we suggested otherwise at MODVIS 2015. Here, we provide additional empirical and theoretical arguments. We then develop arguments that a cluster of complementary, conspicuity representations drive selection, modulated by task goals and history, leading to a blended process that encompasses early, mid-level and late attentional selection and reflects the differences between central and peripheral processes. This design is also constrained by the architectural characteristics of the visual processing pathways, specifically, the boundary problem, as well as retinal photoreceptor distribution. These elements combine into a new strategy for computing fixation targets and a first simulation of its performance is presented.
Start Date
11-5-2016 10:45 AM
End Date
11-5-2016 11:10 AM
Included in
Artificial Intelligence and Robotics Commons, Cognition and Perception Commons, Neurosciences Commons
Focusing on Selection for Fixation
Building on our presentation at MODVIS 2015, we continue in our quest to discover a functional, computational, explanation of the relationship among visual attention, interpretation of visual stimuli, and eye movements, and how these produce visual behavior. Here, we focus on one component, how selection is accomplished for the next fixation. The popularity of saliency map models drives the inference that this is solved; we suggested otherwise at MODVIS 2015. Here, we provide additional empirical and theoretical arguments. We then develop arguments that a cluster of complementary, conspicuity representations drive selection, modulated by task goals and history, leading to a blended process that encompasses early, mid-level and late attentional selection and reflects the differences between central and peripheral processes. This design is also constrained by the architectural characteristics of the visual processing pathways, specifically, the boundary problem, as well as retinal photoreceptor distribution. These elements combine into a new strategy for computing fixation targets and a first simulation of its performance is presented.