• DocumentCode
    2714884
  • Title

    Schematic surface reconstruction

  • Author

    Wu, Changchang ; Agarwal, Sameer ; Curless, Brian ; Seitz, Steven M.

  • Author_Institution
    Univ. of Washington, Seattle, WA, USA
  • fYear
    2012
  • fDate
    16-21 June 2012
  • Firstpage
    1498
  • Lastpage
    1505
  • Abstract
    This paper introduces a schematic representation for architectural scenes together with robust algorithms for reconstruction from sparse 3D point cloud data. The schematic models architecture as a network of transport curves, approximating a floorplan, with associated profile curves, together comprising an interconnected set of swept surfaces. The representation is extremely concise, composed of a handful of planar curves, and easily interpretable by humans. The approach also provides a principled mechanism for interpolating a dense surface, and enables filling in holes in the data, by means of a pipeline that employs a global optimization over all parameters. By incorporating a displacement map on top of the schematic surface, it is possible to recover fine details. Experiments show the ability to reconstruct extremely clean and simple models from sparse structure-from-motion point clouds of complex architectural scenes.
  • Keywords
    edge detection; image reconstruction; complex architectural scenes; dense surface interpolation; floorplan approximation; global optimization; profile curves; schematic models architecture; schematic representation; schematic surface reconstruction; sparse 3D point cloud data reconstruction; sparse structure-from-motion point clouds; transport curves; Image reconstruction; Merging; Noise; Optimization; Robustness; Shape; Surface reconstruction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on
  • Conference_Location
    Providence, RI
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4673-1226-4
  • Electronic_ISBN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2012.6247839
  • Filename
    6247839