• DocumentCode
    456917
  • Title

    Robust Factorisation with Uncertainty Analysis

  • Author

    Brandt, Sami S.

  • Author_Institution
    Lab. of Computational Eng., Helsinki Univ. of Technol.
  • Volume
    1
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    39
  • Lastpage
    42
  • Abstract
    This paper proposes how the classic factorisation algorithm for affine reconstruction can be extended to be robust to outliers and proposes how the uncertainty analysis can be performed in this case. The robust estimation approach elaborated here is based on the iteratively re-weighted least-squares but the use of other robust methods is also discussed. Moreover, the uncertainty analysis presented in this paper could be similarly used in a RANSAC or LMedS extension of the factorisation algorithm. The experiments verify that the proposed approach is reliable and able to give to consistent estimates and uncertainty measure for affine structure and motion
  • Keywords
    image motion analysis; image reconstruction; image sampling; iterative methods; least squares approximations; matrix decomposition; random processes; LMedS; RANSAC; affine reconstruction; factorisation algorithm; iteratively reweighted least-squares; random sampling; uncertainty analysis; Algorithm design and analysis; Iterative algorithms; Laboratories; Motion estimation; Motion measurement; Performance analysis; Pollution measurement; Robustness; Sampling methods; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.1005
  • Filename
    1698828