Fixational eye movements enable robust edge detection.

ABSTRACT: Human vision relies on mechanisms that respond to luminance edges in space and time. Most edge models use orientation-selective mechanisms on multiple spatial scales and operate on static inputs assuming that edge processing occurs within a single fixational instance. Recent studies, however, demonstrate functionally relevant temporal modulations of the sensory input due to fixational eye movements. Here we propose a spatiotemporal model of human edge detection that combines elements of spatial and active vision. The model augments a spatial vision model by temporal filtering and shifts the input images over time, mimicking an active sampling scheme via fixational eye movements. The first model test was White's illusion, a lightness effect that has been shown to depend on edges. The model

SUBMITTER: Schmittwilken L 

PROVIDER: S-EPMC9290315 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature