DocumentCode
2477703
Title
Non-Abelian invariant feature detection
Author
Gur, Yaniv ; Sochen, Nir
Author_Institution
Dept. of Appl. Math., Tel-Aviv Univ., Tel-Aviv
fYear
2008
fDate
8-11 Dec. 2008
Firstpage
1
Lastpage
4
Abstract
We present a novel formulation of non-Abelian invariant feature detection. By choosing suitable measuring functions, we show that the measuring space and the corresponding feature space are equivariant with respect to the SL(2, Ropf) Lie transformation group. This group is non-Abelian and may be decomposed via the Iwasawa decomposition into meaningful transformations on images. We calculate the induced representations of this group on the measuring space. Then, via these representations we construct a set of three PDEs determining an invariant function of the features. We show that this set of equations is solved by the discriminant of a binary form of order n. Hence, the discriminant plays the role of an invariant feature detector with respect to this transformation group.
Keywords
Lie groups; feature extraction; image representation; partial differential equations; Iwasawa decomposition; Lie transformation group; image representation; invariant feature function; nonAbelian invariant feature detection; partial differential equation; Application software; Computer vision; Detectors; Equations; Mathematics; Matrix decomposition; Motion detection; Motion estimation; Pattern recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location
Tampa, FL
ISSN
1051-4651
Print_ISBN
978-1-4244-2174-9
Electronic_ISBN
1051-4651
Type
conf
DOI
10.1109/ICPR.2008.4761230
Filename
4761230
Link To Document