Optimal measurement of visual motion across spatial and temporal scales

TL;DR

This paper presents a normative framework for optimal resource allocation in visual motion measurement, revealing that human contrast sensitivity aligns with the theoretically optimal pattern and explaining phenomena in visual perception.

Contribution

It introduces a new normative model for sensor allocation in visual perception and links it to observed human contrast sensitivity functions.

Findings

Human contrast sensitivity matches the optimal prescription.

The model explains phenomena in visual sensitivity, adaptation, and perceptual organization.

Provides a principled basis for understanding visual motion perception.

Abstract

Sensory systems use limited resources to mediate the perception of a great variety of objects and events. Here a normative framework is presented for exploring how the problem of efficient allocation of resources can be solved in visual perception. Starting with a basic property of every measurement, captured by Gabor's uncertainty relation about the location and frequency content of signals, prescriptions are developed for optimal allocation of sensors for reliable perception of visual motion. This study reveals that a large-scale characteristic of human vision (the spatiotemporal contrast sensitivity function) is similar to the optimal prescription, and it suggests that some previously puzzling phenomena of visual sensitivity, adaptation, and perceptual organization have simple principled explanations.