• DocumentCode
    178247
  • Title

    RGB-D Multi-view System Calibration for Full 3D Scene Reconstruction

  • Author

    Afzal, H. ; Aouada, D. ; Foni, D. ; Mirbach, B. ; Ottersten, B.

  • Author_Institution
    Interdiscipl. Centre for Security, Reliability & Trust Univ. of Luxembourg, Luxembourg
  • fYear
    2014
  • fDate
    24-28 Aug. 2014
  • Firstpage
    2459
  • Lastpage
    2464
  • Abstract
    One of the most crucial requirements for building a multi-view system is the estimation of relative poses of all cameras. An approach tailored for a RGB-D cameras based multi-view system is missing. We propose BAICP+ which combines Bundle Adjustment (BA) and Iterative Closest Point (ICP) algorithms to take into account both 2D visual and 3D shape information in one minimization formulation to estimate relative pose parameters of each camera. BAICP+ is generic enough to take different types of visual features into account and can be easily adapted to varying quality of 2D and 3D data. We perform experiments on real and simulated data. Results show that with the right weighting factor BAICP+ has an optimal performance when compared to BA and ICP used independently or sequentially.
  • Keywords
    calibration; cameras; image colour analysis; image reconstruction; minimisation; pose estimation; 2D visual information; 3D scene reconstruction; 3D shape information; BA algorithm; BAICP+; ICP algorithm; RGB-D camera based multiview system; RGB-D multiview system calibration; bundle adjustment algorithm; camera relative pose estimation; iterative closest point algorithm; minimization formulation; Barium; Calibration; Cameras; Feature extraction; Iterative closest point algorithm; Three-dimensional displays; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2014 22nd International Conference on
  • Conference_Location
    Stockholm
  • ISSN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2014.425
  • Filename
    6977138