• DocumentCode
    2400904
  • Title

    Skeletal graphs for efficient structure from motion

  • Author

    Snavely, Noah ; Seitz, Steven M. ; Szeliski, Richard

  • Author_Institution
    Washington Univ., Seattle, WA
  • fYear
    2008
  • fDate
    23-28 June 2008
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    We address the problem of efficient structure from motion for large, unordered, highly redundant, and irregularly sampled photo collections, such as those found on Internet photo-sharing sites. Our approach computes a small skeletal subset of images, reconstructs the skeletal set, and adds the remaining images using pose estimation. Our technique drastically reduces the number of parameters that are considered, resulting in dramatic speedups, while provably approximating the covariance of the full set of parameters. To compute a skeletal image set, we first estimate the accuracy of two-frame reconstructions between pairs of overlapping images, then use a graph algorithm to select a subset of images that, when reconstructed, approximates the accuracy of the full set. A final bundle adjustment can then optionally be used to restore any loss of accuracy.
  • Keywords
    graph theory; image motion analysis; image reconstruction; image thinning; pose estimation; graph algorithm; image motion; image reconstruction; pose estimation; sampled photo collection; skeletal graph; skeletal image set; Computational geometry; Image reconstruction; Image restoration; Internet; Joints; Layout; Robustness; Time measurement; Uncertainty; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4244-2242-5
  • Electronic_ISBN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2008.4587678
  • Filename
    4587678