• DocumentCode
    3487737
  • Title

    A geometric invariant for visual recognition and 3D reconstruction from two perspective/orthographic views

  • Author

    Shashua, Amnon

  • Author_Institution
    Dept. of Brain & Cognitive Sci., MIT, Cambridge, MA, USA
  • fYear
    1993
  • fDate
    34134
  • Firstpage
    107
  • Lastpage
    117
  • Abstract
    The author addresses the problem of reconstructing 3D space in a projective framework from two views, and the problem of artificially generating novel views of the scene from two given views. He shows that with the correspondences coming from four non-coplanar points in the scene and the corresponding epipoles, one can define and reconstruct (using simple linear methods) a projective invariant, referred to as projective depth, that can be used later to reconstruct the projective or affine structure of the scene, or directly to generate novel views of the scene. The derivation has the advantage that the viewing transformation matrix need not be recovered in the course of computations (i.e., he computes structure without motion)
  • Keywords
    computational geometry; computer vision; image recognition; 3D reconstruction; geometric invariant; novel views; projective depth; projective invariant; reprojection; viewing transformation matrix; visual recognition; Artificial intelligence; Calibration; Cameras; Image recognition; Image reconstruction; Impedance matching; Laboratories; Layout; Predictive models; Stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Qualitative Vision, 1993., Proceedings of IEEE Workshop on
  • Conference_Location
    New York City, NY
  • Print_ISBN
    0-8186-3692-0
  • Type

    conf

  • DOI
    10.1109/WQV.1993.262944
  • Filename
    262944