Skip to main content
Log in

Segment based camera calibration

  • Regular Papers
  • Published:
Journal of Computer Science and Technology Aims and scope Submit manuscript

Abstract

The basic idea of calibrating a camera system in previous approaches is to determine camera parameters by using a set of known 3D points as calibration reference. In this paper, we present a method of camera calibration in which camera parameters are determined by a set of 3D lines. A set of constraints is derived on camera parameters in terms of perspective line mapping. From these constraints, the same perspective transformation matrix as that for point mapping can be computed linearly. The minimum number of calibration lines is 6. This result generalizes that of Liu, Huang and Faugeras[12] for camera location determination in which at least 8 line correspondences are required for linear computation of camera location. Since line segments in an image can be located easily and more accurately than points, the use of lines as calibration reference tends to ease the computation in image preprocessing and to improve calibration accuracy. Experimental results on the calibration along with stereo reconstruction are reported.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. R.O. Duda and P.E. Hart, Parrern Recognition and Scene Analysis. New York, Wiley, 1973.

    Google Scholar 

  2. Y.I. Abdel-Aziz and H.M. Karara, Direct linear transformation into object space coordinates in close-range photogrammetry. Symp. Close-Range Photogrammetry, Univ. of Illinois at Urbana-Champaign, 1–18, 1971.

  3. Y. Yakimovsky and R. Cunningham, A system for extracting three-dimensional measurements form a stereo pair of TV cameras.Computer Graphics and Image Processing, 1978, 7(2), 195–210.

    Article  Google Scholar 

  4. S. Ganapathy, Decomposition of transformation matrices for robot vision. Proc. Int Conf. Robotics, GA, 1984, 130–139.

  5. O.D. Faugeras and G. Toscani, The calibration problem for stereo. Proc. IEEE Conf. Computer vision and Pattern Recognition, Miami, Florida, June 22–26, 1986, 15–20.

  6. W.I Grosky and L.A. Tamburino, A unified approach to the linear camera calibration problem. Proc. Int. Conf. Computer Vision, London, England, June 8–10, 1987, 511–515.

  7. R.Y. Tsai, An efficient and accurate camera calibration technique for 3D machine vision. Proc. IEEE Conf. Computer Vision and Pattern Recognition, Miami, Florida, June 22–26, 1986, 364–374.

  8. A. Mitiche, S. Seida and J.K. Aggarwal, Interpretation of structure and motion from line correspondences. Proc. 8th Int. Conf. Pattern Recognition, Paris, France, Oct. 27–31, 1986.

  9. O.D. Faugeras, F. Lustman and G. Toscani, Motion and structure from point and line matches. Proc. Int. Conf. Computer Vision, London, England, June 8–10, 1987, 25–34.

  10. Y. Liu and T.S. Huang, A linear algorithm for motion estimation using straight line correspondences.Computer Vision, Graphics, and Image Processing, 1988, 44(1), 35–57.

    Article  MathSciNet  Google Scholar 

  11. J. Weng, Y. Liu and T.S. Huang, Estimating motion/structure from line correspondence: robust linear algorithm and unique solution. Proc. IEEE Conf. Computer Vision and Pattern Recognition, Ann Arbor, MI, June 5–9, 1988, 387–392.

  12. J.K. Aggarwal and Y.F. Wang, Analysis of a sequence of images using point and line correspondences. Proc. IEEE Int. Conf. Robotics and Automation, Vol. 3, Raleigh, NC, Mar., 1987, 1275–1280.

    Google Scholar 

  13. Y. Liu, T.S. Huang and O.D. Faugeras, Determination of camera location form 2D to 3D line and point correspondences.IEEE Trans. Pattern Anal. Machine Intell. 1990, 12(1), 28–37.

    Article  Google Scholar 

  14. J. Shen and S. Castan, An optimal linear filter in edge detection. Proc. of the IEEE Conf on Computer Vision and Pattern Recognition, Miami, Florida, June 22–26, 1986, 104–109.

  15. G.Q. Qei and S.D. Ma, Two plane camera calibration: a unified model. Proc. IEEE Conf. on Computer Vision and Pattern Recognition, Hawaii, June 1919, 133–138.

  16. G.Q. Wei and S.D. Ma, Implicit and explicit camera calibration: theory and experiments. Submitted toIEEE Trans. Pattern Anal. Machine Intell. 1992.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ma, S., Wei, G. & Huang, J. Segment based camera calibration. J. of Comput. Sci. & Technol. 8, 11–16 (1993). https://doi.org/10.1007/BF02946581

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02946581

Keywords

Navigation