Abstract
Why does our visual system fail to reconstruct reality, when we look at certain patterns? Where do Geometrical illusions start to emerge in the visual pathway? How far should we take computational models of vision with the same visual ability to detect illusions as we do? This study addresses these questions, by focusing on a specific underlying neural mechanism involved in our visual experiences that affects our final perception. Among many types of visual illusion, ‘Geometrical’ and, in particular, ‘Tilt Illusions’ are rather important, being characterized by misperception of geometric patterns involving lines and tiles in combination with contrasting orientation, size or position. Over the last decade, many new neurophysiological experiments have led to new insights as to how, when and where retinal processing takes place, and the encoding nature of the retinal representation that is sent to the cortex for further processing. Based on these neurobiological discoveries, we provide computer simulation evidence from modelling retinal ganglion cells responses to some complex Tilt Illusions, suggesting that the emergence of tilt in these illusions is partially related to the interaction of multiscale visual processing performed in the retina. The output of our low-level filtering model is presented for several types of Tilt Illusion, predicting that the final tilt percept arises from multiple-scale processing of the Differences of Gaussians and the perceptual interaction of foreground and background elements. The model is a variation of classical receptive field implementation for simple cells in early stages of vision with the scales tuned to the object/texture sizes in the pattern. Our results suggest that this model has a high potential in revealing the underlying mechanism connecting low-level filtering approaches to mid- and high-level explanations such as ‘Anchoring theory’ and ‘Perceptual grouping’.
Highlights
We investigate here whether computational modelling of vision can provide similar interpretation of visual data to our own experiences, based on simple bioplausible modelling of multiscale retinal cell responses to the visual scene
We further explore the neurophysiological model of multiple-scale low-level filtering developed by Nematzadeh et al [14], based on the circular centre and surround mechanism of classical receptive field (CRF) in the retina
We investigated the lateral interaction effect in visual processing of the perceptual organization of pattern elements and how it is connected to mid- and high-level result of grouping factors in our global percept, by simple computational modelling of retinal/cortical simple cells
Summary
We investigate here whether computational modelling of vision can provide similar interpretation of visual data to our own experiences, based on simple bioplausible modelling of multiscale retinal cell responses to the visual scene. Our visual perception of the world is the result of multiple levels of visual processing. Minimal redundancy, with the processing in the retina serving different purposes and operating in different ways from the later processing levels of the cortex. We regard this assumption as fundamental to a biologically plausible vision model, and human-competitive computer vision, reflecting our understanding of human vision. Even given the increasingly detailed biological characterization of both retinal and cortical cells over the last half a century (1960s–2010s), there remains considerable uncertainty, and even some controversy, as to the nature and extent of the encoding of visual information by the retina, and of the subsequent processing and decoding in the cortex (see e.g. the review of physiological retinal findings by Field and Chichilnisky [1] and Golish and Meister [2])
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
