• DocumentCode
    3402435
  • Title

    Motion detail preserving optical flow estimation

  • Author

    Xu, Li ; Jia, Jiaya ; Matsushita, Yasuyuki

  • Author_Institution
    Chinese Univ. of Hong Kong, Hong Kong, China
  • fYear
    2010
  • fDate
    13-18 June 2010
  • Firstpage
    1293
  • Lastpage
    1300
  • Abstract
    We discuss the cause of a severe optical flow estimation problem that fine motion structures cannot always be correctly reconstructed in the commonly employed multi-scale variational framework. Our major finding is that significant and abrupt displacement transition wrecks small-scale motion structures in the coarse-to-fine refinement. A novel optical flow estimation method is proposed in this paper to address this issue, which reduces the reliance of the flow estimates on their initial values propagated from the coarser level and enables recovering many motion details in each scale. The contribution of this paper also includes adaption of the objective function and development of a new optimization procedure. The effectiveness of our method is borne out by experiments for both large- and small-displacement optical flow estimation.
  • Keywords
    image motion analysis; image reconstruction; image sequences; coarse-to-fine refinement; displacement transition; motion detail preserving optical flow estimation; motion structures; multiscale variational framework; objective function; optimization procedure; Asia; Cameras; Councils; Image motion analysis; Motion estimation; Neck; Optical computing; Optical propagation; Robustness; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on
  • Conference_Location
    San Francisco, CA
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4244-6984-0
  • Type

    conf

  • DOI
    10.1109/CVPR.2010.5539820
  • Filename
    5539820