DocumentCode
2679095
Title
Design of multi-parameter steerable functions using cascade basis reduction
Author
Teo, Patrick C. ; Hel-Or, Yacov
Author_Institution
Dept. of Comput. Sci., Stanford Univ., CA, USA
fYear
1998
fDate
4-7 Jan 1998
Firstpage
187
Lastpage
192
Abstract
A new cascade basis reduction method of computing the optimal least-squares set of basis functions to steer a given function is presented. The method combines the Lie group-theoretic and the singular value decomposition approaches such that their respective strengths complement each other. Since the Lie group-theoretic approach is used, the set of basis and steering functions computed can be expressed in analytic form. Because the singular value decomposition method is used, this set of basis and steering functions is optimal in the least-squares sense. Most importantly, the computational complexity in designing basis functions for transformation groups with large numbers of parameters is significantly reduced. The efficiency of the cascade basis reduction method is demonstrated by designing a set of basis functions to steer a Gabor function under the four-parameter linear transformation group
Keywords
Lie groups; computational complexity; singular value decomposition; Gabor function; Lie group; basis functions; cascade basis reduction method; computational complexity; optimal least-squares; singular value decomposition; transformation groups; Adaptive filters; Computer science; Ear; Frequency; Graphics; Kernel; Lighting; Matrix decomposition; Motion estimation; Singular value decomposition;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, 1998. Sixth International Conference on
Conference_Location
Bombay
Print_ISBN
81-7319-221-9
Type
conf
DOI
10.1109/ICCV.1998.710717
Filename
710717
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