• DocumentCode
    254451
  • Title

    3D Reconstruction from Accidental Motion

  • Author

    Yu, F. ; Gallup, David

  • fYear
    2014
  • fDate
    23-28 June 2014
  • Firstpage
    3986
  • Lastpage
    3993
  • Abstract
    We have discovered that 3D reconstruction can be achieved from asingle still photographic capture due to accidental motions of thephotographer, even while attempting to hold the camera still. Although these motions result in little baseline and therefore high depth uncertainty, in theory, we can combine many such measurements over the duration of the capture process (a few seconds) to achieve usable depth estimates. Wepresent a novel 3D reconstruction system tailored for this problemthat produces depth maps from short video sequences from standard cameraswithout the need for multi-lens optics, active sensors, or intentionalmotions by the photographer. This result leads to the possibilitythat depth maps of sufficient quality for RGB-D photography applications likeperspective change, simulated aperture, and object segmentation, cancome "for free" for a significant fraction of still photographsunder reasonable conditions.
  • Keywords
    estimation theory; image colour analysis; image motion analysis; image reconstruction; image sequences; photography; video signal processing; 3D reconstruction; RGB-D photography; accidental motion; depth estimates; depth maps; photographic capture; short video sequences; Cameras; Cost function; Estimation; Image reconstruction; Noise measurement; Three-dimensional displays; Uncertainty; 3D Vision; Multiview Stereo; Structure from Motion;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on
  • Conference_Location
    Columbus, OH
  • Type

    conf

  • DOI
    10.1109/CVPR.2014.509
  • Filename
    6909904