• DocumentCode
    2719010
  • Title

    A theory of multi-layer flat refractive geometry

  • Author

    Agrawal, Amit ; Ramalingam, Srikumar ; Taguchi, Yuichi ; Chari, Visesh

  • fYear
    2012
  • fDate
    16-21 June 2012
  • Firstpage
    3346
  • Lastpage
    3353
  • Abstract
    Flat refractive geometry corresponds to a perspective camera looking through single/multiple parallel flat refractive mediums. We show that the underlying geometry of rays corresponds to an axial camera. This realization, while missing from previous works, leads us to develop a general theory of calibrating such systems using 2D-3D correspondences. The pose of 3D points is assumed to be unknown and is also recovered. Calibration can be done even using a single image of a plane. We show that the unknown orientation of the refracting layers corresponds to the underlying axis, and can be obtained independently of the number of layers, their distances from the camera and their refractive indices. Interestingly, the axis estimation can be mapped to the classical essential matrix computation and 5-point algorithm [15] can be used. After computing the axis, the thicknesses of layers can be obtained linearly when refractive indices are known, and we derive analytical solutions when they are unknown. We also derive the analytical forward projection (AFP) equations to compute the projection of a 3D point via multiple flat refractions, which allows non-linear refinement by minimizing the reprojection error. For two refractions, AFP is either 4th or 12th degree equation depending on the refractive indices. We analyze ambiguities due to small field of view, stability under noise, and show how a two layer system can be well approximated as a single layer system. Real experiments using a water tank validate our theory.
  • Keywords
    calibration; cameras; computational geometry; light refraction; matrix algebra; pose estimation; refractive index; 12th degree equation; 2D-3D correspondences; 3D point projection computation; 4th degree equation; 5-point algorithm; AFP equations; analytical forward projection equations; axial camera; axis estimation; calibration; classical essential matrix computation; layers thicknesses; multilayer flat refractive geometry theory; multiple parallel flat refractive mediums; noise stability; nonlinear refinement; pose estimation; refracting layer orientation; refractive indices; reprojection error minimization; single flat refractive mediums; single layer system; two layer system; Calibration; Cameras; Equations; Estimation; Geometry; Mathematical model; Vectors;
  • 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.2012.6248073
  • Filename
    6248073