• DocumentCode
    254274
  • Title

    3D Shape and Indirect Appearance by Structured Light Transport

  • Author

    O´Toole, Matthew ; Mather, John ; Kutulakos, K.N.

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Toronto, Toronto, ON, Canada
  • fYear
    2014
  • fDate
    23-28 June 2014
  • Firstpage
    3246
  • Lastpage
    3253
  • Abstract
    We consider the problem of deliberately manipulating the direct and indirect light flowing through a time-varying, fully-general scene in order to simplify its visual analysis. Our approach rests on a crucial link between stereo geometry and light transport: while direct light always obeys the epipolar geometry of a projector-camera pair, indirect light overwhelmingly does not. We show that it is possible to turn this observation into an imaging method that analyzes light transport in real time in the optical domain, prior to acquisition. This yields three key abilities that we demonstrate in an experimental camera prototype: (1) producing a live indirect-only video stream for any scene, regardless of geometric or photometric complexity, (2) capturing images that make existing structured-light shape recovery algorithms robust to indirect transport, and (3) turning them into one-shot methods for dynamic 3D shape capture.
  • Keywords
    photometry; stereo image processing; dynamic 3D shape capture; fully general scene; geometric complexity; imaging method; indirect appearance; indirect light manipulation; live indirect only video stream; photometric complexity; stereo geometry; structured light transport; time varying scene; visual analysis; Cameras; Mirrors; Optical imaging; Shape; Streaming media; Three-dimensional displays; 3d shape acquisition; Active triangulation; Coded-exposure imaging; Computational cameras; Computational illumination; Computational video; Depth camera; Indirect illumination; Inter-reflections; Light transport; Structured light; Subsurface scattering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on
  • Conference_Location
    Columbus, OH
  • Type

    conf

  • DOI
    10.1109/CVPR.2014.421
  • Filename
    6909811