Euclidean reconstruction: From paraperspective to perspective

  • Stéphane Christy
  • Radu Horaud
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1065)


In this paper we describe a method to perform Euclidean reconstruction with a perspective camera model. It incrementally performs reconstruction with a paraperspective camera in order to converge towards a perspective model. With respect to other methods that compute shape and motion from a sequence of images with a calibrated perspective camera, this method converges in a few iterations, is computationally efficient, and does not suffer from the non linear nature of the problem. Moreover, the behaviour of the algorithm may be simply explained and analysed, which is an advantage over classical non linear optimization approaches. With respect to 3-D reconstruction using an approximated camera model, our method solves for the sign (reversal) ambiguity in a very simple way and provides much more accurate reconstruction results.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    S. Christy and R. Horaud. A quasi linear reconstruction method from multiple perspective views. In Proc. IROS, pages 374–380, Pittsburgh, Pennsylvania, August 1995.Google Scholar
  2. 2.
    S. Christy and R. Horaud. Euclidean shape and motion from multiple perspective views by affine iterations. IEEE PAMI, 1996.Google Scholar
  3. 3.
    D. F. DeMenthon and L. S. Davis. Model-based object pose in 25 lines of code. Int. J. Comp. Vis., 15(1/2):123–141, 1995.Google Scholar
  4. 4.
    R. I. Hartley. Euclidean reconstruction from uncalibrated views. In Mundy, Zisserman, & Forsyth, editors, Appl. of Inv. in Comp. Vis., pages 237–256. Springer Verlag, 1994.Google Scholar
  5. 5.
    R. Horaud, S. Christy, F. Dornaika, and B. Lamiroy. Object pose: Links between paraperspective and perspective. In 5th ICCV, pages 426–433, Cambridge, Mass., June 1995.Google Scholar
  6. 6.
    C. J. Poelman and T. Kanade. A paraperspective factorization method for shape and motion recovery. In 3rd ECCV, pages 97–108. Stockholm, Sweden, May 1994.Google Scholar
  7. 7.
    L. Quan and R. Mohr. Self-calibration of an affine camera from multiple views. In CAIP'95, pages 448–455, Prague, September 1995.Google Scholar
  8. 8.
    R. Szelinski and S. B. Kang. Recovering 3-D shape and motion from image streams using non-linear least squares. Tech. Rep. CRL 93/3, Digital — Cambr. Res. Lab., March 1993.Google Scholar
  9. 9.
    C. Tomasi and T. Kanade. Shape and motion from image streams under orthography: a factorization method. Int. J. Comp. Vis., 9(2):137–154, November 1992.Google Scholar
  10. 10.
    D. Weinshall. Model-based invariants for 3-d vision. Int. J. Comp. Vis., 10(1):27–42, February 1993.Google Scholar
  11. 11.
    D. Weinshall and C. Tomasi. Linear and incremental acquisition of invariant shape models from image sequences. IEEE PAMI, 17(5):512–517, May 1995.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Stéphane Christy
    • 1
  • Radu Horaud
    • 1
  1. 1.GRAVIR-IMAG & INRIA Rhône-AlpesGrenobleFrance

Personalised recommendations