• DocumentCode
    254671
  • Title

    Separating Texture and Illumination for Single-Shot Structured Light Reconstruction

  • Author

    Vo, Minh ; Narasimhan, Srinivasa G. ; Sheikh, Yaser

  • Author_Institution
    Robot. Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • fYear
    2014
  • fDate
    23-28 June 2014
  • Firstpage
    433
  • Lastpage
    440
  • Abstract
    Active illumination based methods have a trade-off between acquisition time and resolution of the estimated 3D shapes. Multi-shot approaches can generate dense reconstructions but require stationary scenes. In contrast, single-shot methods are applicable to dynamic objects but can only estimate sparse reconstructions and are sensitive to surface texture. In this work, we develop a single-shot approach to produce dense reconstructions of highly textured objects. The key to our approach is an image decomposition scheme that can recover the illumination and the texture images from their mixed appearance. Despite the complex appearances of the illuminated textured regions, our method can accurately compute per pixel warps from the illumination pattern and the texture template to the observed image. The texture template is obtained by interleaving the projection sequence with an all-white pattern. Our estimated warping functions are reliable even with infrequent interleaved projection. Thus, we obtain detailed shape reconstruction and dense motion tracking of the textured surfaces. We validate the approach on synthetic and real data containing subtle non-rigid surface deformations.
  • Keywords
    image motion analysis; image reconstruction; image texture; lighting; shape recognition; dense motion tracking; highly textured object reconstructions; illumination image recovery; image decomposition scheme; image illumination pattern; image texture template; projection sequence interleaving; shape reconstruction; single-shot structured light reconstruction; subtle nonrigid surface deformations; texture image recovery; warping functions; Cameras; Image reconstruction; Lighting; Periodic structures; Shape; Surface texture; Three-dimensional displays;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on
  • Conference_Location
    Columbus, OH
  • Type

    conf

  • DOI
    10.1109/CVPRW.2014.70
  • Filename
    6910018