TY - GEN

T1 - Spatial Simulation of the Muller-Lyer Illusion Genesis with Convolutional Neural Networks

AU - Мамаев, Антон Николаевич

AU - Горбунов, Иван Анатольевич

N1 - Conference code: 14

PY - 2022/10/26

Y1 - 2022/10/26

N2 - The Müller-Lyer illusion is a well-known optical phenomenon with several competing explanations. In the current study we reviewed the illusion in a convolutional neural network from a perspective of image-source relationships in the process of visual functions development. To recreate the effect of the illusion we proposed a novel method that lets us simulate the development of visual functions in a controlled spatial environment from the state of ‘blank slate’ to effective spatial problem solving. This process is designed to reflect the development of human visual system and enable us to determine how depth perception can contribute to the appearance of the phenomenon. We were able to successfully reproduce the effect of the classic Müller-Lyer in 30 independent convolutional models and also get similar results with the variants of the illusion that are thought to be unrelated to spatial perception. For the pairs of classic stimuli we conducted additional statistical analysis using both frequentist and Bayesian methods. The methodological and empirical insights of this study may be helpful for subsequent investigation of visual cognition and reconsideration of the image-source relationships in optical illusions.

AB - The Müller-Lyer illusion is a well-known optical phenomenon with several competing explanations. In the current study we reviewed the illusion in a convolutional neural network from a perspective of image-source relationships in the process of visual functions development. To recreate the effect of the illusion we proposed a novel method that lets us simulate the development of visual functions in a controlled spatial environment from the state of ‘blank slate’ to effective spatial problem solving. This process is designed to reflect the development of human visual system and enable us to determine how depth perception can contribute to the appearance of the phenomenon. We were able to successfully reproduce the effect of the classic Müller-Lyer in 30 independent convolutional models and also get similar results with the variants of the illusion that are thought to be unrelated to spatial perception. For the pairs of classic stimuli we conducted additional statistical analysis using both frequentist and Bayesian methods. The methodological and empirical insights of this study may be helpful for subsequent investigation of visual cognition and reconsideration of the image-source relationships in optical illusions.

KW - Иллюзия Мюллера-Лайера

KW - Нейронные сети

KW - Восприятие

KW - моделирование

UR - https://www.researchgate.net/publication/364894660_Spatial_Simulation_of_the_Muller-Lyer_Illusion_Genesis_with_Convolutional_Neural_Networks

UR - https://www.mendeley.com/catalogue/401e8b6e-7394-3c20-9353-684ca0cbd0da/

U2 - 10.5220/0011529100003332

DO - 10.5220/0011529100003332

M3 - Conference contribution

SN - 978-989-758-611-8

SP - 284

EP - 291

BT - Proceedings of the 14th International Joint Conference on Computational Intelligence - Volume 1: NCTA, 284-291, 2022 , Valletta, Malta

PB - SciTePress

Y2 - 24 October 2022 through 26 October 2022

ER -