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Proceedings Paper

A Bayesian/Geometric Framework For Reconstructing 3-D Shapes In Robot Vision
Author(s): Basilis Gidas; Jose Torreao
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Paper Abstract

We introduce a new Bayesian/Geometric method for estimating orientation and depth from shade and/or texture. The method is based on a prior distribution on the space of all posible (random) surfaces, and a variant of the annealing algorithm for constraint global optimization problems. The method is also useful for partially classifying image contours.

Paper Details

Date Published: 17 May 1989
PDF: 8 pages
Proc. SPIE 1058, High Speed Computing II, (17 May 1989); doi: 10.1117/12.951670
Show Author Affiliations
Basilis Gidas, Brown University (United States)
Jose Torreao, Brown University (United States)

Published in SPIE Proceedings Vol. 1058:
High Speed Computing II
Keith Bromley, Editor(s)

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