DocumentCode
2101619
Title
An eigenvector method for shape-from-shading
Author
Robles-Kelly, Antonio ; Hancock, Edwin R.
Author_Institution
Dept. of Comput. Sci., York Univ., UK
fYear
2003
fDate
17-19 Sept. 2003
Firstpage
474
Lastpage
479
Abstract
We explore how spectral methods for graph seriation can be used to develop a new shape-from-shading algorithm. We characterise the field of surface normals using a transition matrix whose elements are computed from the sectional curvature between different image locations. We use a graph seriation method to define a curvature minimising surface integration path for the purposes of height reconstruction. To smooth the reconstructed surface, we fit quadric patches to the height data. The smoothed surface normal directions are updated ensuring compliance with Lambert´s law. The processes of height recovery and surface normal adjustment are interleaved and iterated until a stable surface is obtained. We provide results on synthetic and real-world imagery.
Keywords
computer vision; eigenvalues and eigenfunctions; graph theory; image reconstruction; iterative methods; matrix algebra; minimisation; Lambert law; computer vision; eigenvector method; graph seriation; height reconstruction; sectional curvature; shape-from-shading; spectral methods; surface normals; transition matrix; Computer science; Computer vision; Concrete; Equations; Image reconstruction; Image segmentation; Sequences; Simulated annealing; Surface fitting; Surface reconstruction;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Analysis and Processing, 2003.Proceedings. 12th International Conference on
Print_ISBN
0-7695-1948-2
Type
conf
DOI
10.1109/ICIAP.2003.1234095
Filename
1234095
Link To Document