• DocumentCode
    3207063
  • Title

    Noise resistant projective and affine invariants

  • Author

    Weiss, Isaac

  • Author_Institution
    Center for Autom. Res., Maryland Univ., College Park, MD, USA
  • fYear
    1992
  • fDate
    15-18 Jun 1992
  • Firstpage
    115
  • Lastpage
    121
  • Abstract
    A method of obtaining local projective and affine invariants that is more robust than existing methods is presented. These shape descriptors are useful for object recognition because they eliminate the search for the unknown viewpoint. Being local, these invariants are much less sensitive to occlusion than the global ones used elsewhere. The basic ideas are (i) using an implicit curve representation without a curve parameter, thus increasing robustness; and (ii) using a canonical coordinate system which is defined by the intrinsic properties of the shape, regardless of any given coordinate system, and is thus invariant. Several configurations are treated: a general curve without any correspondence, and curves with known correspondence of feature points or lines
  • Keywords
    computational geometry; image processing; image recognition; invariance; affine invariants; canonical coordinate system; feature points; implicit curve representation; noise resistant projective invariants; object recognition; occlusion; shape descriptors; Automation; Educational institutions; Face recognition; Libraries; Noise robustness; Noise shaping; Object recognition; Polynomials; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on
  • Conference_Location
    Champaign, IL
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-2855-3
  • Type

    conf

  • DOI
    10.1109/CVPR.1992.223218
  • Filename
    223218