136
Views
0
CrossRef citations to date
0
Altmetric
Reports

An Ecological Approach to Modeling Vision: Quantifying Form Perception Using the Circle Map Equation

, , , &
Pages 41-57 | Published online: 17 Sep 2019
 

Abstract

Object perception occurs within a dynamic world, where the environment and the observer (both body and eyes) are continually moving, shifting and changing. We seek to characterize and quantify this process from a perspective accounting for the interconnected system of motion in the environment, the perceiver and the eye, unfolding through time. Specifically, we build a mathematical representation for object perception based off the circle map equation. We describe an interaction between the eyes’ movement and the movement in the world, in order to better understand how those work together to result in perception. Across three experiments, we show that the stability of the relationship between object perception and complex eye movements can be perturbed and will have a predictable response to said perturbations. In so doing, we provide a different context – a dynamical systems framework – under which we can begin to consider the ecological validity of visual perception models, while recognizing the degree to which the visuo-spatial world is continuously being perturbed and disrupted. In fact, we postulate that such perturbations are capitalized on by the perceptual system, contributing to accurate object and motion identification.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 303.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.