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Modeling Images of Natural 3D Surfaces: Overview and Potential ApplicationsGenerative models of natural images have long been used in computer vision. However, since they only describe the of 2D scenes, they fail to capture all the properties of the underlying 3D world. Even though such models are sufficient for many vision tasks a 3D scene model is when it comes to inferring a 3D object or its characteristics. In this paper, we present such a generative model, incorporating both a multiscale surface prior model for surface geometry and reflectance, and an image formation process model based on realistic rendering, the computation of the posterior model parameter densities, and on the critical aspects of the rendering. We also how to efficiently invert the model within a Bayesian framework. We present a few potential applications, such as asteroid modeling and Planetary topography recovery, illustrated by promising results on real images.
Document ID
20040081117
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Jalobeanu, Andre (NASA Ames Research Center Moffett Field, CA, United States)
Kuehnel, Frank (NASA Ames Research Center Moffett Field, CA, United States)
Stutz, John (NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
September 7, 2013
Publication Date
January 1, 2004
Subject Category
Theoretical Mathematics
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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