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Proceedings Paper

Biological basis for space-variant sensor design I: parameters of monkey and human spatial vision
Author(s): Alan S. Rojer; Eric L. Schwartz
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Paper Abstract

Biological sensor design has long provided inspiration for sensor design in machine vision. However relatively little attention has been paid to the actual design parameters provided by biological systems as opposed to the general nature of biological vision architectures. In the present paper we will provide a review of current knowledge of primate spatial vision design parameters and will present recent experimental and modeling work from our lab which demonstrates that a numerical conformal mapping which is a refinement of our previous complex logarithmic model provides the best current summary of this feature of the primate visual system. In this paper we will review recent work from our laboratory which has characterized some of the spatial architectures of the primate visual system. In particular we will review experimental and modeling studies which indicate that: . The global spatial architecture of primate visual cortex is well summarized by a numerical conformal mapping whose simplest analytic approximation is the complex logarithm function . The columnar sub-structure of primate visual cortex can be well summarized by a model based on a band-pass filtered white noise. We will also refer to ongoing work in our lab which demonstrates that: . The joint columnar/map structure of primate visual cortex can be modeled and summarized in terms of a new algorithm the ''''proto-column'''' algorithm. This work provides a reference-point for current engineering approaches to novel architectures for

Paper Details

Date Published: 1 February 1991
PDF: 13 pages
Proc. SPIE 1382, Intelligent Robots and Computer Vision IX: Neural, Biological, and 3D Methods, (1 February 1991); doi: 10.1117/12.25205
Show Author Affiliations
Alan S. Rojer, New York Univ. (United States)
Eric L. Schwartz, New York Univ. (United States)

Published in SPIE Proceedings Vol. 1382:
Intelligent Robots and Computer Vision IX: Neural, Biological, and 3D Methods
David P. Casasent, Editor(s)

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