Motion Illusions Generated Using Predictive Neural Networks Also Fool Humans

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Sinapayen, Lana, Watanabe, Eiji
Format: Preprint
Published: 2021
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866912942799192064
author Sinapayen, Lana
Watanabe, Eiji
author_facet Sinapayen, Lana
Watanabe, Eiji
contents Why do we sometimes perceive static images as if they were moving? Visual motion illusions enjoy a sustained popularity, yet there is no definitive answer to the question of why they work. Here we present evidence in favor of the hypothesis that illusory motion is a side effect of the predictive abilities of the brain. We present a generative model, the Evolutionary Illusion GENerator (EIGen), that creates new visual motion illusions based on a video predictive neural network. We confirm that the constructed illusions are effective on human participants through a psychometric survey. Our results support the hypothesis that illusory motion might be the consequence of perceiving the brain's own predictions rather than perceiving raw visual input from the eyes. The philosophical motivation of this paper is to call attention to the untapped potential of "motivated failures", ways for artificial systems to fail as biological systems fail, as a worthy outlet for Artificial Intelligence and Artificial Life research.
format Preprint
id arxiv_https___arxiv_org_abs_2112_13243
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Motion Illusions Generated Using Predictive Neural Networks Also Fool Humans
Sinapayen, Lana
Watanabe, Eiji
Neural and Evolutionary Computing
Artificial Intelligence
Computer Vision and Pattern Recognition
Why do we sometimes perceive static images as if they were moving? Visual motion illusions enjoy a sustained popularity, yet there is no definitive answer to the question of why they work. Here we present evidence in favor of the hypothesis that illusory motion is a side effect of the predictive abilities of the brain. We present a generative model, the Evolutionary Illusion GENerator (EIGen), that creates new visual motion illusions based on a video predictive neural network. We confirm that the constructed illusions are effective on human participants through a psychometric survey. Our results support the hypothesis that illusory motion might be the consequence of perceiving the brain's own predictions rather than perceiving raw visual input from the eyes. The philosophical motivation of this paper is to call attention to the untapped potential of "motivated failures", ways for artificial systems to fail as biological systems fail, as a worthy outlet for Artificial Intelligence and Artificial Life research.
title Motion Illusions Generated Using Predictive Neural Networks Also Fool Humans
topic Neural and Evolutionary Computing
Artificial Intelligence
Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2112.13243