KEYWORDS: Organisms, Human-machine interfaces, Genetic algorithms, Visualization, Visual system, Personal digital assistants, Bayesian inference, Human vision and color perception, Diodes, Resistors
Does natural selection favor veridical perceptions, those that more accurately depict the objective environment? Vision researchers often claim that it does. But this claim, though influential, has not been adequately tested. In this paper we formalize the claim and a few alternatives. We then discuss the results of evolutionary games and genetic algorithms that indicate that veridical perceptions can be driven to extinction by non-veridical strategies that are tuned to fitness rather than to objective reality. This suggests that natural selection need not favor veridical perceptions, and that the effects of natural selection on perception deserve further study. We then address the question: How can an organism act effectively in an environment that it does not perceive veridically? (Acknowledgement: Brian Marion and Kyle Stevens are collaborators in this research.)
KEYWORDS: Human vision and color perception, Visualization, 3D image processing, Medical imaging, Diagnostics, Image compression, Human vision research, Image processing, Visual system, Medical research
Human vision, for the purpose of shape recognition, decomposes three-dimensional shapes into subunits. Simple rules, stated in the language of differential geometry, can describe this decomposition.
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