DocumentCode :
1559077
Title :
Shape from periodic texture using the eigenvectors of local affine distortion
Author :
Ribeiro, Eraldo ; Hancock, Edwin R.
Author_Institution :
Dept. of Comput. Sci., York Univ., UK
Volume :
23
Issue :
12
fYear :
2001
fDate :
12/1/2001 12:00:00 AM
Firstpage :
1459
Lastpage :
1465
Abstract :
Shows how the local slant and tilt angles of regularly textured curved surfaces can be estimated directly, without the need for iterative numerical optimization. We work in the frequency domain and measure texture distortion using the affine distortion of the pattern of spectral peaks. The key theoretical contribution is to show that the directions of the eigenvectors of the affine distortion matrices can be used to estimate local slant and tilt angles of tangent planes to curved surfaces. In particular, the leading eigenvector points in the tilt direction. Although not as geometrically transparent, the direction of the second eigenvector can be used to estimate the slant direction. The required affine distortion matrices are computed using the correspondences between spectral peaks, established on the basis of their energy ordering. We apply the method to a variety of real-world and synthetic imagery
Keywords :
eigenvalues and eigenfunctions; image texture; matrix algebra; parameter estimation; spectral analysis; eigenanalysis; eigenvectors; frequency domain; local affine distortion; local slant angles; local tilt angles; regularly textured curved surfaces; shape from periodic texture; spectral analysis; spectral peaks; synthetic imagery; texture distortion; Distortion measurement; Frequency domain analysis; Frequency measurement; Geometrical optics; Image segmentation; Psychology; Shape; Spectral analysis; Surface texture; Transmission line matrix methods;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.977570
Filename :
977570
Link To Document :
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