• DocumentCode
    3333485
  • Title

    Optical Flow Estimation Using Laplacian Mesh Energy

  • Author

    Wenbin Li ; Cosker, D. ; Brown, Michael ; Rui Tang

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Bath, Bath, UK
  • fYear
    2013
  • fDate
    23-28 June 2013
  • Firstpage
    2435
  • Lastpage
    2442
  • Abstract
    In this paper we present a novel non-rigid optical flow algorithm for dense image correspondence and non-rigid registration. The algorithm uses a unique Laplacian Mesh Energy term to encourage local smoothness whilst simultaneously preserving non-rigid deformation. Laplacian deformation approaches have become popular in graphics research as they enable mesh deformations to preserve local surface shape. In this work we propose a novel Laplacian Mesh Energy formula to ensure such sensible local deformations between image pairs. We express this wholly within the optical flow optimization, and show its application in a novel coarse-to-fine pyramidal approach. Our algorithm achieves the state-of-the-art performance in all trials on the Garg et al. dataset, and top tier performance on the Middlebury evaluation.
  • Keywords
    computer graphics; computer vision; image registration; image sequences; mesh generation; shape recognition; Laplacian mesh energy; Middlebury evaluation; coarse-to-fine pyramidal approach; computer vision research; dense image correspondence; graphics research; image pairs; local smoothness; local surface shape preservation; nonrigid deformation preservation; nonrigid optical flow algorithm; nonrigid registration; optical flow estimation; optical flow optimization; Computer vision; Estimation; Image edge detection; Laplace equations; Optical imaging; Optimization; Vectors; Laplacian Mesh; Optical Flow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on
  • Conference_Location
    Portland, OR
  • ISSN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2013.315
  • Filename
    6619159