• DocumentCode
    3326117
  • Title

    Sparse depth estimation using multi-view 3D modeling

  • Author

    Li, Jinjin ; Karam, Lina J.

  • Author_Institution
    Sch. of Electr., Comput. & Energy Eng., Arizona State Univ., Tempe, AZ, USA
  • fYear
    2012
  • fDate
    12-14 Jan. 2012
  • Firstpage
    151
  • Lastpage
    154
  • Abstract
    This paper presents a 2D to 3D conversion system from multiple views based on the computation of a sparse depth map. This method is able to deal with the multiple views obtained from uncalibrated hand-held cameras without prior knowledge of the camera parameters or scene geometry. The obtained reconstructed sparse depth maps of feature points in 3D scenes provide accurate relative depth information of the objects. Sample ground-truth depth data points are used to calculate a scale factor in order to estimate the true depth by scaling the obtained relative depth using the estimated scale factor. Results are presented to illustrate the performance of the developed system. It is shown that the implemented 2D to 3D conversion system results in a reconstructed depth map that matches the ground-truth depth data.
  • Keywords
    cameras; image reconstruction; 2D conversion system; 3D conversion system; 3D reconstruction; ground-truth depth data points; multiview 3D modeling; sparse depth estimation; uncalibrated hand-held cameras; Cameras; Estimation; Feature extraction; Geometry; Image reconstruction; Measurement; Three dimensional displays; 3D reconstruction; Depth estimation; Euclidean reconstruction; Multi-view; Sparse depth map;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Signal Processing Applications (ESPA), 2012 IEEE International Conference on
  • Conference_Location
    Las Vegas, NV
  • Print_ISBN
    978-1-4673-0899-1
  • Type

    conf

  • DOI
    10.1109/ESPA.2012.6152468
  • Filename
    6152468