• DocumentCode
    3277815
  • Title

    Quadratic formulation of disparity estimation problem for light-field camera

  • Author

    Tulyakov, Sergey ; Tae Hee Lee ; Heechul Han

  • Author_Institution
    DMC R&D, Samsung Electron., Suwon, South Korea
  • fYear
    2013
  • fDate
    15-18 Sept. 2013
  • Firstpage
    2063
  • Lastpage
    2067
  • Abstract
    Newly available light-field (LF) cameras are able to capture several views of a scene simultaneously. These views typically have small parallax, and thus can be easily registered. In this paper we exploit this property of the views captured by the LF camera to formulate disparity estimation problem as a quadratic energy minimization problem. Our problem formulation has three benefits. Firstly, it allows computation of continuous disparity with subpixel accuracy. Secondly it permits recovering disparity of loosely textured objects and ensures that the disparity boundaries are aligned with the object´s boundaries. And, finally, it allows finding the solution very quickly. It takes 15-20s for our non-optimized Matlab code to compute the solution for 25 × 350 × 350 input views.
  • Keywords
    cameras; image texture; LF camera; continuous disparity; disparity boundaries; disparity estimation problem; disparity recovery; light-field camera; loosely-textured objects; nonoptimized Matlab code; object boundaries; parallax; quadratic energy minimization problem; quadratic formulation; subpixel accuracy; Bayesian formulation; depth; disparity; light-field; plenoptic; quadratic energy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2013 20th IEEE International Conference on
  • Conference_Location
    Melbourne, VIC
  • Type

    conf

  • DOI
    10.1109/ICIP.2013.6738425
  • Filename
    6738425