Title :
A Bayesian approach to high resolution 3D surface reconstruction from multiple images
Author :
Morris, Robin D. ; Cheeseman, Peter ; Smelyanskiy, Vadim N. ; Maluf, David A.
Author_Institution :
NASA Ames Res. Center, Moffett Field, CA, USA
Abstract :
We present a radically different approach to the recovery of the three dimensional geometric and reflectance properties of a surface from image data. We pose the problem in a Bayesian framework, and proceed to infer the parameters of the model describing the surface. This allows great flexibility in the specification of the model, in terms of how both the geometrical properties and surface reflectance are specified. In the usual manner for Bayesian approaches it requires that we can simulate the data that would have been recorded for any state of the model in order to infer the model. The theoretical aspects are thus very general. We present rules for one type of surface geometry (the triangular mesh) and for the Lambertian model of light scattering. Our framework also allows the easy incorporation of data from multiple sensing modalities
Keywords :
Bayes methods; image reconstruction; image resolution; light scattering; reflectivity; surface reconstruction; Bayesian approach; Lambertian model; geometrical properties; high resolution 3D surface reconstruction; light scattering; multiple images; multiple sensing modalities; surface geometry; three dimensional geometric properties; three dimensional reflectance properties; triangular mesh; Bayesian methods; Cameras; Geometry; Image reconstruction; Image resolution; NASA; Read only memory; Reflectivity; Satellites; Surface reconstruction;
Conference_Titel :
Higher-Order Statistics, 1999. Proceedings of the IEEE Signal Processing Workshop on
Conference_Location :
Caesarea
Print_ISBN :
0-7695-0140-0
DOI :
10.1109/HOST.1999.778711
