• 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