Motion signals deflect relative positions of moving objects

Watanabe, Eiji; Matsunaga, Wataru; Kitaoka, Akiyoshi

doi:10.1016/j.neures.2010.07.1200

Cited by 2 publications

(2 citation statements)

References 33 publications

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“…We first calculated predicted illusory flows for each MIDD using a DNN model generated as a human vision simulator [28]. The network structure of this study's model implemented [20] prediction hypotheses derived from the physiology and anatomy of the cerebral cortex and psychophysics [7,12,25,27]. It was trained with first-person view videos, and as a result, it successfully simulated human illusory perception induced by the RSI [28].…”

Section: Dnn Model Experimentsmentioning

confidence: 99%

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

Kobayashi¹,

Watanabe²

2021

Preprint

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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.Preprint. Under review.

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Section: Dnn Model Experimentsmentioning

confidence: 99%

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

Kobayashi¹,

Watanabe²

2021

Preprint

Self Cite

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“…Our research group has studied motion illusion by attempting to reproduce illusions using DNNs and comparing them with human perception. We previously focused on the relationship between the occurrence of an illusion and the predictive function of the brain [Watanabe et al, 2010]. In that study, we constructed a DNN model incorporating predictive coding theory [Lotter et al, 2017] as a theoretical model of the cerebrum [Kawato et al, 1993, Rao and Ballard, 1999, Friston, 2005 and trained by first-person-viewed videos [Watanabe et al, 2018].…”

Section: Introductionmentioning

confidence: 99%

Motion illusion-like patterns extracted from photo and art images using predictive deep neural networks

Kobayashi

Kitaoka

Kosaka

et al. 2022

Sci Rep

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In our previous study, we successfully reproduced the illusory motion perceived in the rotating snakes illusion using deep neural networks incorporating predictive coding theory. In the present study, we further examined the properties of the network using a set of 1500 images, including ordinary static images of paintings and photographs and images of various types of motion illusions. Results showed that the networks clearly classified a group of illusory images and others and reproduced illusory motions against various types of illusions similar to human perception. Notably, the networks occasionally detected anomalous motion vectors, even in ordinally static images where humans were unable to perceive any illusory motion. Additionally, illusion-like designs with repeating patterns were generated using areas where anomalous vectors were detected, and psychophysical experiments were conducted, in which illusory motion perception in the generated designs was detected. The observed inaccuracy of the networks will provide useful information for further understanding information processing associated with human vision.

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Motion signals deflect relative positions of moving objects

Cited by 2 publications

References 33 publications

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

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

Motion illusion-like patterns extracted from photo and art images using predictive deep neural networks

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