17 May 1989 A Bayesian/Geometric Framework For Reconstructing 3-D Shapes In Robot Vision
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Proceedings Volume 1058, High Speed Computing II; (1989); doi: 10.1117/12.951670
Event: OE/LASE '89, 1989, Los Angeles, CA, United States
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.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Basilis Gidas, Jose Torreao, "A Bayesian/Geometric Framework For Reconstructing 3-D Shapes In Robot Vision", Proc. SPIE 1058, High Speed Computing II, (17 May 1989); doi: 10.1117/12.951670; https://doi.org/10.1117/12.951670
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KEYWORDS
Optimization (mathematics)

Annealing

Data modeling

Image processing

Nickel

Detection and tracking algorithms

Light sources

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