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 :
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