Skip to main content
Log in

Structure from motion using line correspondences

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

Abstract

A theory is presented for the computation of three-dimensional motion and structure from dynamic imagery, using only line correspondences. The traditional approach of corresponding microfeatures (interesting points-highlights, corners, high-curvature points, etc.) is reviewed and its shortcomings are discussed. Then, a theory is presented that describes a closed form solution to the motion and structure determination problem from line correspondences in three views. The theory is compared with previous ones that are based on nonlinear equations and iterative methods.

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. B.K.P.Horn and B.G.Schunck, “Determining optical flow,” Artificial Intelligence 17: 185–204, 1981.

    Google Scholar 

  2. S. Ullman and E. Hildreth, “The measurement of visual motion,” Physical and Biological Processing of Images (Proc. Intern. Symp., Rank Prize Funds. London), O.J. Braddick and A.C. Sleigh (eds.), Springer-Verlag, pp. 154–176, September 1982.

  3. H.H.Nagel, “Displacement vectors derived from second order intensity variations in image sequences,” Comput. Vision, Graphics, and Image Process. 21: 85–117, 1983.

    Google Scholar 

  4. S. Ullman, “The interpretation of visual motion.” Ph.D. thesis, 1977.

  5. A. Bandopadhay, Ph.D. thesis, Department of Computer Science, University of Rochester, 1986.

  6. G. Adiv, “Determining 3-D motion and structure from optical flow generated from several moving objects,” COINS Tech. Rept. 84-07, July 1984.

  7. A.Bruss and B.K.P.Horn, “Passive navigation,” Comput. Vision, Graphics, and Image Process. 21: 3–20, 1983.

    Google Scholar 

  8. H.C.Longuet-Higgins and K.Prazdny, “The interpretation of a moving retinal image,” Proc. Roy. Soc. London B 208: 385–397, 1980.

    Google Scholar 

  9. H.C.Longuet-Higgins, “A computer algorithm for reconstructing a scene from two projections,” Nature 293: 133–135, 1981.

    Google Scholar 

  10. K.Prazdny, “Egomotion and relative depth map from optical flow,” Biol. Cybernetics 36: 87–102, 1980.

    Google Scholar 

  11. K.Prazdny, “Determining the instantaneous direction of motion from optical flow generated by a curvilinearly moving observer,” Comput. Vision, Graphics, and Image Process. 17: 94–97, 1981.

    Google Scholar 

  12. R.Y.Tsai and T.S.Huang, “Uniqueness and estimation of three dimensional motion parameters of rigid objects.” In Image Understanding 1984, S.Ullman and W.Richards (eds.). Ablex Publishing: Norwood, NJ, 1984.

    Google Scholar 

  13. R.Y.Tsai and T.S.Huang, “Uniqueness and estimation of three dimensional motion parameters of rigid objects with curved surfaces,” IEEE Trans. PAMI 6: 13–27, 1984.

    Google Scholar 

  14. J. Aloimonos, “Low level visual computations.” Ph.D. thesis, Department of Computer Science, University of Rochester, August 1986.

  15. E. Ito and J. Aloimonos, “Computing transformation parameters from images,” Proc. IEEE Conf. on Robotics and Automation, 1987.

  16. S. Negadahripour. Ph.D. thesis, AI Lab, MIT, 1986.

  17. S.Ullman, “Analysis of visual motion by biological and computer systems,” IEEE Comput. 14: 57–69, 1981.

    Google Scholar 

  18. Y. Liu and T.S. Huang, “Estimation of rigid body motion using straight line correspondences,” Proc. Intern. Conf. Pattern Recog., Paris, October 1986.

  19. Y. Liu and T.S. Huang, “Estimation of rigid body motion using straight line correspondences,” IEEE Workshop on Motion: Representation and Analysis, Kiawah Island, SC, May 1986.

  20. G.W.Stewart, Introduction to Matrix Computations, Academic Press, San Diego, CA, 1980.

    Google Scholar 

  21. M.E.Spetsakis and J.Y.Aloimonos, “Closed form solution to the structure from motion problem from line correspondences,” TR-1798, Computer Vision Laboratory, Center for Automation Research, University of Maryland, College Park, March 1987.

    Google Scholar 

  22. B.K.P. Horn, “The Binford-Horn edge finder,” MIT AI Memo 285, December 1973.

  23. J. Canny, M.S. thesis, Artificial Intelligence Laboratory, MIT, 1984.

  24. J.B.Burns, A.R.Hanson, and E.M.Riseman, “Extracting straight lines,” IEEE Trans. PAMI 8: 425–455, July 1986.

    Google Scholar 

  25. W.H.Press, B.P.Flannery, S.A.Teukolsky, and W.T.Vetterling, Numerical Recipes in C: The Art of Scientific Computing. Cambridge University Press: New York, 1988.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Spetsakis, M.E., Aloimonos, J.(. Structure from motion using line correspondences. Int J Comput Vision 4, 171–183 (1990). https://doi.org/10.1007/BF00054994

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00054994

Keywords

Navigation