Visual Search Asymmetry: Deep Nets and Humans Share Similar Inherent Biases.

ABSTRACT: Visual search is a ubiquitous and often challenging daily task, exemplified by looking for the car keys at home or a friend in a crowd. An intriguing property of some classical search tasks is an asymmetry such that finding a target A among distractors B can be easier than finding B among A. To elucidate the mechanisms responsible for asymmetry in visual search, we propose a computational model that takes a target and a search image as inputs and produces a sequence of eye movements until the target is found. The model integrates eccentricity-dependent visual recognition with target-dependent top-down cues. We compared the model against human behavior in six paradigmatic search tasks that show asymmetry in humans. Without prior exposure to the stimuli or task-specific training, the model p

SUBMITTER: Gupta SK 

PROVIDER: S-EPMC9436507 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature