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66
A Provably Convergent Method for the Non-Linear Image Irradiance Equation
, 1996
"... In this paper we present a provably convergent method for the Shape from Shading problem in the case of a Lambertian reflectance map. The non-linear image irradiance equation is approximated by a Taylor-expansion. The resulting linear PDE is solved numerically by an implicit, sequentiell method. We ..."
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In this paper we present a provably convergent method for the Shape from Shading problem in the case of a Lambertian reflectance map. The non-linear image irradiance equation is approximated by a Taylor-expansion. The resulting linear PDE is solved numerically by an implicit, sequentiell method. We
A New Method Fo Solving The Image Irradiance Equation Using Characteristics
"... . In this paper we show how a large class of fully nonlinear Hamilton-Jacobi Equations can be rewritten as quasilinear equations using a natural change of variables. The technique becomes especially simple for the Eikonal Equation in the classical Shape from Shading problem. When solving this equati ..."
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. In this paper we show how a large class of fully nonlinear Hamilton-Jacobi Equations can be rewritten as quasilinear equations using a natural change of variables. The technique becomes especially simple for the Eikonal Equation in the classical Shape from Shading problem. When solving
E(x,y) Fig. 1. Light direction �p fixed for w ∈ S. Y 2
"... Shape from Shading: surface S from image intensity E. Sfs is modeled by image irradiance equation (IIE) R(ux, uy) = E(x, y). Reflectance map: reflectance properties of S. ..."
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Shape from Shading: surface S from image intensity E. Sfs is modeled by image irradiance equation (IIE) R(ux, uy) = E(x, y). Reflectance map: reflectance properties of S.
Symmetric Shape-from-Shading Using Self-ratio Image
- INT’L J. COMPUTER VISION
, 2001
"... In this paper, we present a symmetric shape-from-shading (SFS) approach to recover both shape and albedo for symmetric objects. Lambertian surfaces with unknown varying albedo and orthographic projections are assumed. In our formulation of symmetric SFS, wehave two image irradiance equations. One i ..."
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Cited by 31 (2 self)
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In this paper, we present a symmetric shape-from-shading (SFS) approach to recover both shape and albedo for symmetric objects. Lambertian surfaces with unknown varying albedo and orthographic projections are assumed. In our formulation of symmetric SFS, wehave two image irradiance equations. One
Numerical Shape from Shading and Occluding Boundaries
- Artifical Intelligence
, 1981
"... An iterative method for computing shape from shading using occluding boundary information is proposed. Some applications of this method are shown. We employ the stereographic plane to express the orientations of surface patches, rather than the more commonly.used gradient space. Use of the stereogra ..."
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Cited by 254 (20 self)
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the smoothness constraints and the image-irradiance equation iteratively, using occluding boundary information to supply boundary conditions. Good initial values are found at certain points to help reduce the number of iterations required to reach a reasonable solution. Numerical experiments show that the method
Reconstruction of medical images by perspective shape-from-shading
- Proc. ICPR’04, 3:778 – 781
, 2004
"... Shape-from-Shading (SfS) is a fundamental problem in Computer Vision; it is based upon the image irradiance equation. Recently, the authors proposed to solve the image irradiance equation under the assumption of perspective projection rather than the common orthographic one. The solution was a modif ..."
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Cited by 5 (0 self)
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Shape-from-Shading (SfS) is a fundamental problem in Computer Vision; it is based upon the image irradiance equation. Recently, the authors proposed to solve the image irradiance equation under the assumption of perspective projection rather than the common orthographic one. The solution was a
A new perspective [on] Shape-from-Shading
, 2003
"... Shape-from-Shading (SfS) is a fundamental problem in Computer Vision. The vast majority of research in this field have assumed orthography as its projection model. This paper re-examines the basis of SfS, the image irradiance equation, under an assumption of perspective projection. The paper also sh ..."
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Cited by 26 (2 self)
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Shape-from-Shading (SfS) is a fundamental problem in Computer Vision. The vast majority of research in this field have assumed orthography as its projection model. This paper re-examines the basis of SfS, the image irradiance equation, under an assumption of perspective projection. The paper also
Perspective shape-from-shading by fast marching
- IEEE Conf. on Computer Vision and Pattern Recognition 1
, 2004
"... Shape-from-Shading (SfS) is a fundamental problem in Computer Vision. At its basis lies the image irradiance equation. Recently, the authors proposed to base the image irradiance equation on the assumption of perspective projection rather than the common orthographic one. The current paper presents ..."
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Cited by 22 (2 self)
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Shape-from-Shading (SfS) is a fundamental problem in Computer Vision. At its basis lies the image irradiance equation. Recently, the authors proposed to base the image irradiance equation on the assumption of perspective projection rather than the common orthographic one. The current paper presents
An Evidence Combining Approach to Shape-from-shading
"... In this paper we describe a statistical framework for shape-from-shading. First, we commence by making least squares estimates of local Hessian matrices using samples of surface normals. These estimated Hessians are used to perform parallel transport of the surface normals across the surface. By tra ..."
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. By transporting neighbouring surface normals in this way we are able collect samples of votes for the surface normal direction at each location. We select between these alternatives on the basis of compliance with the image irradiance equation. 1.
Analytic Bilinear Appearance Subspace Construction for Modeling Image Irradiance Under Natural Illumination and Non-Lambertian Reflectance
"... Conventional subspace construction approaches suffer from the need of “large-enough ” image ensemble render-ing numerical methods intractable. In this paper, we pro-pose an analytic formulation for low-dimensional subspace construction in which shading cues lie while preserving the natural structure ..."
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structure of an image sample. Using the frequency-space representation of the image irradiance equation, the process of finding such subspace is cast as establishing a relation between its principal components and that of a de-terministic set of basis functions, termed as irradiance har-monics. Representing
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