Projective geometry and its applications to computer graphics
Projective geometry and its applications to computer graphics
Shape and motion of nonrigid bodies
Computer Vision, Graphics, and Image Processing
Robot Vision
Computer Vision
SHAPE FROM SHADING: A METHOD FOR OBTAINING THE SHAPE OF A SMOOTH OPAQUE OBJECT FROM ONE VIEW
SHAPE FROM SHADING: A METHOD FOR OBTAINING THE SHAPE OF A SMOOTH OPAQUE OBJECT FROM ONE VIEW
Generating Semantic Descriptions From Drawings of Scenes With Shadows
Generating Semantic Descriptions From Drawings of Scenes With Shadows
Shape-from-Shading Under Perspective Projection
International Journal of Computer Vision
A Shape-from-Shading Method of Polyhedral Objects Using Prior Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Generic and Provably Convergent Shape-from-Shading Method for Orthographic and Pinhole Cameras
International Journal of Computer Vision
Shape from shading for the digitization of curved documents
Machine Vision and Applications
Numerical methods for shape-from-shading: A new survey with benchmarks
Computer Vision and Image Understanding
3D-spline reconstruction using shape from shading: Spline from shading
Image and Vision Computing
A Multi-Image Shape-from-Shading Framework for Near-Lighting Perspective Endoscopes
International Journal of Computer Vision
Reconstructing convex polygons and polyhedra from edge and face counts in orthogonal projections
FSTTCS'07 Proceedings of the 27th international conference on Foundations of software technology and theoretical computer science
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A shape-from-shading analysis for a single perspective image of a polyhedron is presented. Given a single perspective image of a polyhedron, the depth of any point of the polyhedron from the camera, the direction of the light source illuminating the polyhedron and the albedo of the polyhedron, a system of algebraic equations are derived, which, when combined with edge information, quantitatively describes the shape of the polyhedron. This analysis is best possible in the sense that if any component of what the author has assumed is omitted, no similar analysis can provide the same results.