• DocumentCode
    3590017
  • Title

    3D Mixed Invariant and its Application on Object Classification

  • Author

    Feng, Songhe ; Aouada, Djamila ; Krim, H. ; Kogan, I.

  • Author_Institution
    Dept. of ECE, NCSU, Raleigh, NC, USA
  • Volume
    1
  • fYear
    2007
  • Abstract
    A new integro-differential invariant for curves in 3D transformed by affine group action is presented in this paper. The derivatives involved are of the first order, and therefore this invariant is significantly less sensitive to noise than classical affine differential invariants, the simplest of which involves derivatives of order 5. A classification procedure based on characteristic curves of an object surface is considered using our proposed mixed invariants. Substantiating examples are provided to verify efficiency and discriminant power of the characteristic spatial curve based 3D object classification.
  • Keywords
    image classification; integro-differential equations; object detection; 3D mixed invariant; affine group action; discriminant power; integro-differential invariant; object classification; spatial curve; Application software; Computational complexity; Computer vision; Face recognition; Feature extraction; Noise robustness; Object recognition; Pattern recognition; Shape; Turning; 3D affine transformation; affine invariant; invariant feature; object classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    1-4244-0727-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.2007.366716
  • Filename
    4217116