• DocumentCode
    3407425
  • Title

    Model evolution: An incremental approach to non-rigid structure from motion

  • Author

    Zhu, Shengqi ; Zhang, Li ; Smith, Brandon M.

  • Author_Institution
    Univ. of Wisconsin-Madison, Madison, WI, USA
  • fYear
    2010
  • fDate
    13-18 June 2010
  • Firstpage
    1165
  • Lastpage
    1172
  • Abstract
    In this paper, we present a new framework for non-rigid structure from motion (NRSFM) that simultaneously addresses three significant challenges: severe occlusion, perspective camera projection, and large non-linear deformation. We introduce a concept called a model graph, which greatly reduces the computational cost of discovering groups of input images that depict consistent 3D shapes. A 3D model is constructed for each input image by traversing the model graph along multiple evolutionary paths. A compressive shape representation is constructed, which (1) consolidates the multiple 3D models for each image reconstructed during model evolution and (2) reduces the number of models needed to represent the input image set. Assuming feature correspondences are known, we demonstrate our algorithm on both real and synthetic data sets that exemplify all three aforementioned challenges.
  • Keywords
    computer graphics; image motion analysis; image representation; 3D model; compressive shape representation; consistent 3D shapes; input image set represention; large nonlinear deformation; model evolution; multiple evolutionary paths; nonrigid structure from motion; perspective camera projection; severe occlusion; Cameras; Computational efficiency; Computer vision; Deformable models; Face; Image coding; Image reconstruction; Large-scale systems; Robustness; Shape;
  • 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.2010.5540085
  • Filename
    5540085