Improved methods of estimating shape from shading using the light source coordinate system
Artificial Intelligence
A Method for Enforcing Integrability in Shape from Shading Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Shape from shading
Height and gradient from shading
International Journal of Computer Vision
CVGIP: Image Understanding
Shape from shading as a partially well-constrained problem
CVGIP: Image Understanding
A viscosity solutions approach to shape-from-shading
SIAM Journal on Numerical Analysis
Measuring and modeling anisotropic reflection
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Tracking level sets by level sets: a method for solving the shape from shading problem
Computer Vision and Image Understanding
Generalization of the Lambertian model and implications for machine vision
International Journal of Computer Vision
Computer Vision and Image Understanding
Shape from shading with a generalized reflectance map model
Computer Vision and Image Understanding
Improved Diffuse Reflection Models for Computer Vision
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Illumination for computer generated pictures
Communications of the ACM
Optimal Algorithm for Shape from Shading and Path Planning
Journal of Mathematical Imaging and Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
"Perspective Shape from Shading" and Viscosity Solutions
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Lax-Friedrichs sweeping scheme for static Hamilton-Jacobi equations
Journal of Computational Physics
Surface Normals and Height from Non-Lambertian Image Data
3DPVT '04 Proceedings of the 3D Data Processing, Visualization, and Transmission, 2nd International Symposium
Shape from Shading: A Well-Posed Problem?
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A New Formulation for Shape from Shading for Non-Lambertian Surfaces
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
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Many different shape from shading (SFS) algorithms have emerged during the last three decades. Recently, we proposed [1] a unified framework that is capable of solving the SFS problem under various settings of imaging conditions representing the image irradiance equation of each setting as an explicit Partial Differential Equation (PDE). However, the result of any SFS algorithm is mainly affected by errors in the given image brightness, either due to image noise or modeling errors. In this paper, we are concerned with quantitatively assessing the degree of robustness of our unified approach with respect to these errors. Experimental results have revealed promising performance against noisy images but has also lacked in reconstructing the correct shape due to error in the modeling process. This result emphasizes the need for robust algorithms for surface reflectance estimation to aid SFS algorithms producing more realistic shapes.