Motion Illusions Generated Using Predictive Neural Networks Also Fool Humans
This work addresses a fundamental question in visual perception for cognitive science and AI, offering insights into brain function and suggesting new research directions in artificial systems.
The paper tackled the problem of why static images can be perceived as moving by proposing that motion illusions arise from the brain's predictive abilities, and it developed a generative model (EIGen) that creates new illusions, which were confirmed effective on humans in a survey.
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.