A method for shape-from-shading using multiple images acquired under different viewing and lighting conditions
- 7 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 10 (10636919) , 53-60
- https://doi.org/10.1109/cvpr.1989.37828
Abstract
A novel formulation for shape-from-shading from multiple images acquired under different viewing and lighting conditions is presented. The method is based on using an explicit image formation model to create renditions of the surface being estimated, which are synthetic versions of the observed images. It is applicable in a variety of imaging situations, including those involving unknown nonuniform albedo. A probabilistic model is developed based on typical characteristics of the surface and minimizing the difference between the synthetic and observed images. This model is used to arrive at Bayesian formulation of the shape-from-shading problem. Techniques are presented to compute an estimate that is statistically optimal in the sense that it is the expected value of the surface, given the set of observations derived from it. The method is applied to Viking imagery of Mars.Keywords
This publication has 11 references indexed in Scilit:
- Digital imagery analysis of unusual Martian surface featuresApplied Optics, 1988
- Probabilistic Solution of Ill-Posed Problems in Computational VisionJournal of the American Statistical Association, 1987
- Signal matching through scale spaceInternational Journal of Computer Vision, 1987
- Modeling and Segmentation of Noisy and Textured Images Using Gibbs Random FieldsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1987
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of ImagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1984
- Microcanonical Monte Carlo SimulationPhysical Review Letters, 1983
- Hill shading and the reflectance mapProceedings of the IEEE, 1981
- Generalized photoclinometry for Mariner 9Icarus, 1975
- Fractional Brownian Motions, Fractional Noises and ApplicationsSIAM Review, 1968
- Monte Carlo MethodsPublished by Springer Nature ,1964