• DocumentCode
    926530
  • Title

    Invariant fitting of two view geometry

  • Author

    Torr, P.H.S. ; Fitzgibbon, A.W.

  • Author_Institution
    Sch. of Math. & Comput., Oxford Brookes Univ., UK
  • Volume
    26
  • Issue
    5
  • fYear
    2004
  • fDate
    5/1/2004 12:00:00 AM
  • Firstpage
    648
  • Lastpage
    650
  • Abstract
    This paper describes an extension of Bookstein´s and Sampson´s methods, for fitting conics, to the determination of epipolar geometry, both in the calibrated case, where the Essential matrix E is to be determined or in the uncalibrated case, where we seek the fundamental matrix F. We desire that the fitting of the relation be invariant to Euclidean transformations of the image, and show that there is only one suitable normalization of the coefficients and that this normalization gives rise to a quadratic form allowing eigenvector methods to be used to find E or F, or an arbitrary homography H. The resulting method has the advantage that it exhibits the improved stability of previous methods for estimating the epipolar geometry, such as the preconditioning method of Hartley, while also being invariant to equiform transformations.
  • Keywords
    computational geometry; curve fitting; eigenvalues and eigenfunctions; image motion analysis; least squares approximations; matrix algebra; Bookstein methods; Essential matrix; Euclidean transformations; Hartley preconditioning method; Sampson methods; conics; eigenvector methods; epipolar geometry; equiform transformations; fundamental matrix; homography; image motion analysis; invariant fitting; least squares approximations; normalization; quadratic form; two-view geometry; Calibration; Cameras; Eigenvalues and eigenfunctions; Fitting; Geometry; Image analysis; Least squares approximation; Least squares methods; Motion analysis; Stability; Algorithms; Artificial Intelligence; Cluster Analysis; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Photogrammetry; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2004.1273967
  • Filename
    1273967