Authors:
Nasim Nematzadeh
1
;
Trent W. Lewis
1
and
David M. W. Powers
2
Affiliations:
1
Flinders University, Australia
;
2
Flinders University and Beijing University of Technology, Australia
Keyword(s):
Visual Perception, Cognitive Systems, Pattern Recognition, Biological Neural Networks, Self-organising Systems, Geometrical Illusions, Tilt Effects, Difference of Gaussian.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Cognitive Systems
;
Computational Intelligence
;
Evolutionary Computing
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Symbolic Systems
;
Theory and Methods
;
Vision and Perception
Abstract:
Visual illusions emerge as an attractive field of research with the discovery over the last century of a variety of deep and mysterious mechanisms of visual information processing in the human visual system. Among many classes of visual illusion relating to shape, brightness, colour and motion, “geometrical illusions” are essentially based on the misperception of orientation, size, and position. The main focus of this paper is on illusions of orientation, sometimes referred to as “tilt illusions”, where parallel lines appear not to be parallel, a straight line is perceived as a curved line, or angles where lines intersect appear larger or smaller. Although some low level and high level explanations have been proposed for geometrical tilt illusions, a systematic explanation based on model predictions of both illusion magnitude and local tilt direction is still an open issue. Here a neurophysiological model is expounded based on Difference of Gaussians implementing a classical receptiv
e field model of retinal processing that predicts tilt illusion effects.
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