• DocumentCode
    3299249
  • Title

    Noise in bilinear problems

  • Author

    Haddon, J.A. ; Forsyth, D.A.

  • Author_Institution
    Div. of Comput. Sci., California Univ., Berkeley, CA, USA
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    622
  • Abstract
    Despite the wide application of bilinear problems to problems both in computer vision and in other fields, their behaviour under the effects of noise is still poorly understood. In this paper, we show analytically that marginal distributions on the solution components of a bilinear problem can be bimodal, even with Gaussian measurement error. We demonstrate and compare three different methods of estimating the covariance of a solution. We show that the Hessian at the mode substantially underestimates covariance. Many problems in computer vision can be posed as bilinear problems: i.e. one must find a solution to a set of equations of the form
  • Keywords
    Gaussian noise; bilinear systems; computer vision; Gaussian measurement error; Hessian; bilinear problems; computer vision; covariance; solution components; Application software; Computer errors; Computer science; Computer vision; Equations; Gaussian noise; Image reconstruction; Motion analysis; Noise measurement; Optical scattering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7695-1143-0
  • Type

    conf

  • DOI
    10.1109/ICCV.2001.937684
  • Filename
    937684