Advertisement

Camera calibration of a head-eye system for active vision

  • Mengxiang Li
Stereo and Calibration
Part of the Lecture Notes in Computer Science book series (LNCS, volume 800)

Abstract

In this paper, we present methods and techniques for calibrating cameras of a head-eye system, which has computer controlled focusing, zooming, and iris. The idea is to build up look-up-tables for intrinsic parameters so we can index them. Extensive experiments were carried out and results are reported here.

Keywords

Focal Length Camera Calibration Intrinsic Parameter Optical Center Principal Point 
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.
    ASP. Manual of Photogrammetry. American Society for Photogrammetry, 4th edition, 1984.Google Scholar
  2. 2.
    B. Caprile and V. Torre. Using vanishing points for camera calibration. International Journal of Computer Vision, 4:127–140, April 1990.Google Scholar
  3. 3.
    T. Echigo. A camera calibration technique using three sets of parallel lines. Machine Vision and Applications, 3:159–167, March 1990.Google Scholar
  4. 4.
    K. Kanatani and Y. Onodera. Noise robust camera calibration using vanishing points. IEICE Transaction on Information and Systems, E74(10), October 1991.Google Scholar
  5. 5.
    J. M. Lavest, G. Rives, and M. Dhome. 3D reconstruction by zooming. IEEE Robotics and Automation (to appear), 1993.Google Scholar
  6. 6.
    M. X. Li. Camera calibration of the KTH head-eye system. Technical report, CVAP-147, NADA, KTH., March 1994.Google Scholar
  7. 7.
    M.X. Li and Demetrios Betsis. Kinematic calibration of a binocular head-eye system for active vision. Technical report, (in prep.), CVAP, NADA, KTH, 1994.Google Scholar
  8. 8.
    K. Pahlavan and J.O. Eklundh. A head-eye system — analysis and design. CVGIP: Image Understanding, 56(1):41–56, July 1992.Google Scholar
  9. 9.
    K. Pahlavan, T. Uhlin, and J.O. Eklundh. Active vision as a methodology. In J. Y. Aloimonos, editor, Active Perception, Advances in Computers. Lawrence-Erlbaum, 1993.Google Scholar
  10. 10.
    K. Tarabanis, R. Y. Tsai, and D. S. Goodman. Modeling of a computer-controlled zoom lens. In IEEE International Conference on Robotics and Automation, pages 1545–1551, Nice, France, May 1992.Google Scholar
  11. 11.
    Roger Y. Tsai. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE Joural of Robotics and Automation, RA-3(4):323–331, August 1987.Google Scholar
  12. 12.
    L. Wang and W. Tsai. Computing camera parameters using vanishing-line information from a rectangular parallelepiped. Machine Vision and Applications, 3:129–141, March 1990.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Mengxiang Li
    • 1
  1. 1.Computational Vision and Active Perception Laboratory (CVAP) Department of Numerical Analysis and Computing ScienceRoyal Institute of Technology (KTH)StockholmSweden

Personalised recommendations