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Telecentric optics for computational vision

  • Masahiro Watanabe
  • Shree K. Nayar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1065)

Abstract

An optical approach to constant-magnification imaging is described. Magnification variations due to changes in focus setting pose problems for pertinent vision techniques, such as, depth from defocus. It is shown that magnification of a conventional lens can be made invariant to defocus by simply adding an aperture at an analytically derived location. The resulting optical configuration is called “telecentric.” It is shown that most commercially available lenses can be turned into telecentric ones. The procedure for calculating the position of the additional aperture is outlined. The photometric and geometric properties of telecentric lenses are discussed in detail. Several experiments have been conducted to demonstrate the effectiveness of telecentricity.

Keywords

Zoom Lens Scene Point Sensor Plane Focus Setting Image Side 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    M. Born and E. Wolf. Principles of Optics. London:Permagon, 1965.Google Scholar
  2. 2.
    V. M. Bove, Jr. Entropy-based depth from focus. Journal of Optical Society of America A, 10:561–566, April 1993.Google Scholar
  3. 3.
    T. Darrell and K. Wohn. Pyramid based depth from focus. Proc. of IEEE Conf. on Computer Vision and Pattern Recognition, pages 504–509, June 1988.Google Scholar
  4. 4.
    J. Ens and P. Lawrence. A matrix based method for determining depth from focus. Proc. of IEEE Conf. on Computer Vision and Pattern Recognition, pages 600–609, June 1991.Google Scholar
  5. 5.
    B. K. P. Horn. Focusing. Technical Report Memo 160, AI Lab., Massachusetts Institute of Technology, Cambridge, MA, USA, 1968.Google Scholar
  6. 6.
    B. K. P. Horn. Robot Vision. The MIT Press, 1986.Google Scholar
  7. 7.
    R. A. Jarvis. A perspective on range finding techniques for computer vision. IEEE Trans. on Pattern Analysis and Machine Intelligence, 5(2):122–139, March 1983.Google Scholar
  8. 8.
    R. Kingslake. Optical System Design. Academic Press, 1983.Google Scholar
  9. 9.
    A. Krishnan and N. Ahuja. Range estimation from focus using a non-frontal imaging camera. Proc. of AAAI Conf., pages 830–835, July 1993.Google Scholar
  10. 10.
    E. Krotkov. Focusing. International Journal of Computer Vision, 1:223–237, 1987.Google Scholar
  11. 11.
    S. K. Nayar and Y. Nakagawa. Shape from focus. IEEE Trans. on Pattern Analysis and Machine Intelligence, 16(8):824–831, August 1994.Google Scholar
  12. 12.
    S. K. Nayar and M. Watanabe. Passive bifocal vision sensor. Technical Report (in preparation), Dept. of Computer Science, Columbia University, New York, NY, USA, October 1995.Google Scholar
  13. 13.
    S. K. Nayar, M. Watanabe, and M. Noguchi. Real-time focus range sensor. Proc. of Intl. Conf. on Computer Vision, pages 995–1001, June 1995.Google Scholar
  14. 14.
    A. Pentland. A new sense for depth of field. IEEE Trans. on Pattern Analysis and Machine Intelligence, 9(4):523–531, July 1987.Google Scholar
  15. 15.
    G. Surya and M. Subbarao. Depth from defocus by changing camera aperture: A spatial domain approach. Proc. of IEEE Conf. on Computer Vision and Pattern Recognition, pages 61–67, June 1993.Google Scholar
  16. 16.
    M. Watanabe and S. K. Nayar. Telecentric optics for constant-magnification imaging. Technical Report CUCS-026-95, Dept. of Computer Science, Columbia University, New York, NY, USA, September 1995.Google Scholar
  17. 17.
    R. G. Willson and S. A. Shafer. Modeling and calibration of automated zoom lenses. Technical Report CMU-RI-TR-94-03, The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA, January 1994.Google Scholar
  18. 18.
    Y. Xiong and S. A. Shafer. Moment and hypergeometric filters for high precision computation of focus, stereo and optical flow. Technical Report CMU-RI-TR-94-28, The Robotics Institute, Carnegie Mellon University, Pittsburg, PA, USA, September 1994.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Masahiro Watanabe
    • 1
  • Shree K. Nayar
    • 2
  1. 1.Production Engineering Research Lab.Hitachi Ltd.YokohamaJapan
  2. 2.Department of Computer ScienceColumbia UniversityNew YorkUSA

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