A Simple Visual Model Accounts for Drift Illusion and Reveals Illusory Patterns

  • Daiki NakamuraEmail author
  • Shunji Satoh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9950)


Computational models of vision should not only be able to reproduce experimentally obtained results; such models should also be able to predict the input–output properties of vision. We assess whether a simple computational model of neurons in the Middle Temporal (MT) visual area proposed by the authors can account for illusory perception of “rotating drift patterns,” by which humans perceive illusory rotation (clockwise or counterclockwise) depending on the background luminance. Moreover, to predict whether a pattern causes visual illusion or not, we generate an enormous set of possible visual patterns as inputs to the MT model: \( 8^{8} = 16,777,216, \) possible input patterns. Numerical quantities of model outputs by computer simulation for 88 inputs were used to estimate human illusory perception. Using psychophysical experiments, we show that the model prediction is consistent with human perception.


Visual illusion Lucas–Kanade method MT Computational model 



This work was partially supported by JSPS KAKENHI (24500371 and 16K00204) and NIJC Riken, JAPAN.


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Graduate School of Information SystemsThe University of Electro-CommunicationsTokyoJapan

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