Branching Gaussian Process Models for Computer Vision
Bayesian methods provide a principled approach to some of the hardest problems in computer vision—low signal-to-noise ratios, ill-posed problems, and problems with missing data. This dissertation applies Bayesian modeling to infer multidimensional continuous manifolds (e.g., curves, surfaces) from i...
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| Language: | en_US |
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The University of Arizona.
2016
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| Online Access: | http://hdl.handle.net/10150/612094 http://arizona.openrepository.com/arizona/handle/10150/612094 |