• DocumentCode
    3401758
  • Title

    3D curve sketch: Flexible curve-based stereo reconstruction and calibration

  • Author

    Fabbri, Ricardo ; Kimia, Benjamin

  • fYear
    2010
  • fDate
    13-18 June 2010
  • Firstpage
    1538
  • Lastpage
    1545
  • Abstract
    Interest point-based multiview 3D reconstruction and calibration methods have been very successful in select applications but are not applicable when an abundance of feature points are not available. They also lead to an unorganized point cloud reconstruction where the geometry of the scene is not explicit. The multiview stereo methods on the other hand yield dense surface geometry but require a highly controlled or calibrated setting. We propose and develop a novel framework for 3D reconstruction and calibration based on image curve content, whose output is a 3D curve sketch, an unorganized set of 3D curve fragments. This approach, which is meant to augment the previous approaches, results in a reconstruction of geometric curve structure which can serve as a scaffold on which surface patches can be potentially reconstructed. It is intented for the setting where a number of images are available with coarsely calibrated cameras. The approach operates in two stages. A reliable partial 3D curve sketch is first reconstructed and this is used to refine the cameras to yield a more complete 3D curve sketch in a second stage. A key advantage of this approach is the ability to integrate information across a large number of views. The results have been evaluated on a few datasets.
  • Keywords
    computational geometry; image reconstruction; stereo image processing; 3D curve sketch; calibration; flexible curve-based stereo reconstruction; image curve content; interest point-based multiview 3D reconstruction; multiview stereo method; point cloud reconstruction; surface geometry; Calibration; Cameras; Clouds; Computer vision; Geometry; Image reconstruction; Layout; Stereo image processing; Stereo vision; Surface reconstruction;
  • 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.2010.5539787
  • Filename
    5539787