A neuro-mathematical model for geometrical optical illusions
This work addresses the challenge of understanding low-level visual processing for researchers in neuroscience and computational vision, but it is incremental as it builds on prior models.
The authors tackled the problem of modeling geometrical optical illusions by developing a mathematical model and computational algorithm based on an existing geometrical framework, which qualitatively reproduces the perceived misperceptions in visual stimuli.
Geometrical optical illusions have been object of many studies due to the possibility they offer to understand the behaviour of low-level visual processing. They consist in situations in which the perceived geometrical properties of an object differ from those of the object in the visual stimulus. Starting from the geometrical model introduced by Citti and Sarti in [3], we provide a mathematical model and a computational algorithm which allows to interpret these phenomena and to qualitatively reproduce the perceived misperception.