Artificial Perception Meets Psychophysics, Revealing a Fundamental Law of Illusory Motion

TL;DR

This study combines psychophysics and neural network modeling to uncover a fundamental law behind the Rotating Snakes illusion, showing how color and luminance influence perceived motion.

Contribution

It introduces a new fundamental law explaining the illusion's mechanism, integrating psychophysics and deep learning approaches.

Findings

The four-color illusion's strength is enhanced by combining two three-color motion vectors.

Deep neural networks can effectively model human perceptual phenomena.

A fundamental law of illusory motion was discovered.

Abstract

Rotating Snakes is a visual illusion in which a stationary design is perceived to move dramatically. In the current study, the mechanism that generates perception of motion was analyzed using a combination of psychophysics experiments and deep neural network models that mimic human vision. We prepared three- and four-color illusion-like designs with a wide range of luminance and measured their strength of induced rotational motion. As a result, we discovered the fundamental law that the effect of the four-color snake rotation illusion was successfully enhanced by the combination of two perceptual motion vectors produced by the two three-color designs. In years to come, deep neural network technology will be one of the most effective tools not only for engineering applications but also for human perception research.