• DocumentCode
    791924
  • Title

    Accurate dense optical flow estimation using adaptive structure tensors and a parametric model

  • Author

    Liu, Haiying ; Chellappa, Rama ; Rosenfeld, Azriel

  • Author_Institution
    Center for Autom. Res., Univ. of Maryland, College Park, MD, USA
  • Volume
    12
  • Issue
    10
  • fYear
    2003
  • Firstpage
    1170
  • Lastpage
    1180
  • Abstract
    An accurate optical flow estimation algorithm is proposed in this paper. By combining the three-dimensional (3D) structure tensor with a parametric flow model, the optical flow estimation problem is converted to a generalized eigenvalue problem. The optical flow can be accurately estimated from the generalized eigenvectors. The confidence measure derived from the generalized eigenvalues is used to adaptively adjust the coherent motion region to further improve the accuracy. Experiments using both synthetic sequences with ground truth and real sequences illustrate our method. Comparisons with classical and recently published methods are also given to demonstrate the accuracy of our algorithm.
  • Keywords
    adaptive estimation; eigenvalues and eigenfunctions; image sequences; parameter estimation; tensors; 3D structure tensor; accuracy; adaptive structure tensors; coherent motion region; confidence measure; dense optical flow estimation; generalized eigenvalue problem; generalized eigenvectors; ground truth; parametric flow model; parametric model; real sequences; synthetic sequences; three-dimensional structure tensor; Adaptive optics; Biomedical optical imaging; Eigenvalues and eigenfunctions; Image motion analysis; Motion analysis; Motion estimation; Nonlinear optics; Optical sensors; Parametric statistics; Tensile stress;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/TIP.2003.815296
  • Filename
    1233560