• DocumentCode
    1379241
  • Title

    A Self-Calibrating Method for Photogeometric Acquisition of 3D Objects

  • Author

    Aliaga, Daniel G. ; Xu, Yi

  • Author_Institution
    Dept. of Comput. Sci., Purdue Univ., West Lafayette, IN, USA
  • Volume
    32
  • Issue
    4
  • fYear
    2010
  • fDate
    4/1/2010 12:00:00 AM
  • Firstpage
    747
  • Lastpage
    754
  • Abstract
    We present a self-calibrating photogeometric method using only off-the-shelf hardware that enables quickly and robustly obtaining multimillion point-sampled and colored models of real-world objects. Some previous efforts use a priori calibrated systems to separately acquire geometric and photometric information. Our key enabling observation is that a digital projector can be simultaneously used as either an active light source or as a virtual camera (as opposed to a digital camera, which cannot be used for both). We present our self-calibrating and multiviewpoint 3D acquisition method, based on structured light, which simultaneously obtains mutually registered surface position and surface normal information and produces a single high-quality model. Acquisition processing freely alternates between using a geometric setup and using a photometric setup with the same hardware configuration. Further, our approach generates reconstructions at the resolution of the camera and not only the projector. We show the results of capturing several high-quality models of real-world objects.
  • Keywords
    calibration; cameras; computer vision; image registration; 3D objects; a priori calibrated systems; acquisition processing; digital projector; multiviewpoint 3D acquisition method; self-calibrating photogeometric method; surface position registration; virtual camera; Digital cameras; Hardware; Image analysis; Image reconstruction; Light sources; Photometry; Robustness; Shape; Solid modeling; Surface reconstruction; Digitization and image capture; geometric modeling.; scene analysis;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2009.202
  • Filename
    5374411