• 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