Skip to main content
Log in

Theory and Practice of Projective Rectification

  • Published:
International Journal of Computer Vision Aims and scope Submit manuscript

Abstract

This paper gives a new method for image rectification, the process of resampling pairs of stereo images taken from widely differing viewpoints in order to produce a pair of “matched epipolar projections”. These are projections in which the epipolar lines run parallel with the x-axis and consequently, disparities between the images are in the x-direction only. The method is based on an examination of the fundamental matrix of Longuet-Higgins which describes the epipolar geometry of the image pair. The approach taken is consistent with that advocated by Faugeras (1992) of avoiding camera calibration. The paper uses methods of projective geometry to determine a pair of 2D projective transformations to be applied to the two images in order to match the epipolar lines. The advantages include the simplicity of the 2D projective transformation which allows very fast resampling as well as subsequent simplification in the identification of matched points and scene reconstruction.

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

  • Ayache, N. and Hansen, C. 1988. Rectification of images for binocular and trinocular stereovision. In Proc. 9th International Conference on Pattern Recognition, Rome, pp. 11–16.

  • Ayache, N. and Lustman, F. 1991. Trinocular stereo vision for robotics. IEEE Transactions on PAMI, 13(1):73–85.

    Google Scholar 

  • Courtney, P., Thacker, N.A., and Brown, C.R. 1992. A hardware architecture for image rectification and ground plane obstacle avoidance. In Proc. 11th IAPR, ICPR, pp. 23–26.

  • Rudolf Sturm Das Problem der Projektivität und seine Anwendung auf die Flächen zweiten Grades. Math. Ann., 1:533–574, 1869.

    Google Scholar 

  • Faugeras, O. 1992. What can be seen in three dimensions with an uncalibrated stereo rig?. In Proc. of ECCV-92, G. Sandini (Ed.), Vol. 588, LNCS-Series, Springer-Verlag, pp. 563–578.

  • Faugeras, O. and Maybank, S. 1990. Motion from point matches: Multiplicity of solutions. International Journal of Computer Vision, 4:225–246.

    Google Scholar 

  • Faugeras, O.D., Luong, Q.-T., and Maybank, S.J. 1992. Camera self-calibration: Theory and experiments. In Proc. of ECCV-92, G. Sandini (Ed.), Vol. 588, LNCS-Series, Springer-Verlag, pp. 321–334.

  • Hartley, R. 1992. Estimation of relative camera positions for uncalibrated cameras. In Proc. of ECCV-92, G. Sandini (Ed.), Vol. 588, LNCS-Series, Springer-Verlag, pp. 579–587.

  • Hartley, R. 1993. Cheirality invariants. In Proc. Darpa Image Understanding Workshop, pp. 745–753.

  • Hartley, R., Gupta, R., and Chang, T. 1992. Stereo from uncalibrated cameras. In Proceedings Computer Vision and Pattern Recognition Conference (CVPR-92).

  • Longuet-Higgins, H.C. 1981. A computer algorithm for reconstructing a scene from two projections. Nature, 293.

  • Mohr, R., Veillon, F., and Quan, L. 1993. Relative 3D reconstruction using multiple uncalibrated images. In Proc. CVPR-93, pp. 543–548.

  • Papadimitriou, D.V. and Dennis, T.J. 1996. Epipolar line estimation and rectification for stereo image pairs. IEEE Transactions on Image Processing, 5(4):672–676.

    Google Scholar 

  • Press, W.H., Flannery, B.P., Teukolsky, S.A., and Vetterling, W.T. 1988. Numerical Recipes in C. Cambridge University Press: Cambridge, England.

    Google Scholar 

  • Robert, L., Buffa, M., and Hébert, M. 1995. Weakly-calibrated stereo perception for Rover navigation. In Proc. 5th International Conference on Computer Vision, Cambridge, MA, pp. 46–51.

  • Rodin, V. and Ayache, A. 1994. Axial stereovision: Modelization and comparison between two calibration methods. In Proc. ICIP-94, pp. 725–729.

  • Shevlin, F. 1994. Resampling of scanned imagery for rectification and registration. In Proc. ICIP-94, pp. 1007–1011.

  • Slama, C.C. (Ed.). 1980. Manual of Photogrammetry, Fourth Edition. American Society of Photogrammetry: Falls Church, VA.

    Google Scholar 

  • Toutin, T. and Carbonneau, Y. 1992. MOS and SEASAT image geometric corrections. IEEE Transactions on Geoscience and Remote Sensing, 30(3):603–609

    Google Scholar 

  • Wolberg, G. 1990. Digital Image Warping. IEEE Computer Society Press: Los Alamitos, CA.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hartley, R.I. Theory and Practice of Projective Rectification. International Journal of Computer Vision 35, 115–127 (1999). https://doi.org/10.1023/A:1008115206617

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1008115206617

Navigation