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Proceedings Paper

Stereo vision using Gabor receptive fields
Author(s): Michael A. Gennert; Jonathan A. Malin
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Paper Abstract

This paper presents the extraction of depth data from stereo image pairs using a nontraditional stereo algorithm taken from computational neuroscience. The technique is based on the workings of the mammalian visual system, using the Gabor representation of an image to mimic the filtering properties of simple and complex cells in the visual cortex. Gabor- transformed images afford an alternate stereo correlation method that, though computationally intensive, is well-suited for solution in parallel. This implementation computes the Gabor transform of input images by sampling at four distinct frequencies and computing correlation at each frequency. We consider four methods of combining the resulting four correlation measures and present results of testing the algorithm on random dot and real image stereograms.

Paper Details

Date Published: 1 November 1992
PDF: 12 pages
Proc. SPIE 1826, Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods, (1 November 1992); doi: 10.1117/12.131587
Show Author Affiliations
Michael A. Gennert, Worcester Polytechnic Institute (United States)
Jonathan A. Malin, Worcester Polytechnic Institute (United States)

Published in SPIE Proceedings Vol. 1826:
Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods
David P. Casasent, Editor(s)

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