Saliency Map Models for Stimulus-Driven Mechanisms in Visual Search: Neural and Functional Accounts
Saliency map models have been influential in neurocognitive modeling of visual attention. Despite recent applications to complex visual scenes, some basic characteristics of the model remain elusive. Here, we address two issues; neural plausibility of saliency computation, and functional account of search asymmetry phenomenon by a saliency map model. With some modifications, we showed that saliency can be computed by a neurally plausible way, and that search asymmetry can be accounted for only by stimulus-driven mechanisms.
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