DocumentCode
2530036
Title
A computational approach to steerable functions
Author
Teo, Patrick C. ; Hel-Or, Yacov
Author_Institution
Dept. of Comput. Sci., Stanford Univ., CA, USA
fYear
1997
fDate
17-19 Jun 1997
Firstpage
313
Lastpage
318
Abstract
We present a computational, group-theoretic approach to steerable functions. The approach is group-theoretic in that the treatment involves continuous transformation groups for which elementary Lie group theory may be applied. The approach is computational in that the theory is constructive and leads directly to a procedural implementation. For functions that are steerable with n finite number of basis functions under a k-parameter group, the procedure is efficient and is guaranteed to return the minimum number of basis functions. If the function is not steerable, a numerical implementation of the procedure could also be used to compute basis functions that approximately steer the function over a range of transformation parameters. Examples of both applications are demonstrated
Keywords
Lie groups; functions; image processing; numerical analysis; polynomials; trees (mathematics); basis functions; computational approach; computer vision; continuous transformation groups; elementary Lie group theory; group theory; image processing; k-parameter group; numerical implementation; polynomials; steerable functions; transformation parameters; trees; Application software; Computer graphics; Computer science; Computer vision; Convolution; Image processing; Kernel; Linear systems; NASA; Nonlinear filters;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on
Conference_Location
San Juan
ISSN
1063-6919
Print_ISBN
0-8186-7822-4
Type
conf
DOI
10.1109/CVPR.1997.609341
Filename
609341
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