Verging Axis Stereophotogrammetry

  • Khurram Jawed
  • John Morris
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7087)


Conventional stereophotogrammetry uses a canonical configuration in which the optical axes of both cameras are parallel. However, if we follow lessons from evolution and swivel the cameras so that their axes intersect in a fixation point, then we obtain considerably better depth resolution. We modified our real-time stereo hardware to handle verging axis configurations and show that the predicted depth resolution is practically obtainable. We compare two techniques for rectifying images for verging configurations. Bouguet’s technique gives a simpler geometry - the iso-disparity lines are straight and the familiar reciprocal relationship between depth and disparity may still be used. However when the iso-disparity lines are the Veith-Muller circles, slightly better depth resolution may be obtained in the periphery of the field of view - at the expense of a more complex conversion from disparity to depth.


Lookup Table Depth Resolution Epipolar Line Stereo Correspondence Vergence Angle 
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.


  1. 1.
    Maybank, S.: Theory of Reconstruction from Image Motion. Springer, Heidelberg (1993)CrossRefzbMATHGoogle Scholar
  2. 2.
    Meissner, G.: Beitrge zur Physiologie des Sehorgans. Leipzig, Engelmann (1854)Google Scholar
  3. 3.
    Aguilonii, F.: Opticorum Libri Sex philosophis juxta ac mathematicis utiles. Antwerp (1613)Google Scholar
  4. 4.
    Pollefeys, M., Sinha, S.: Iso-Disparity Surfaces for General Stereo Configurations. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004, Part III. LNCS, vol. 3023, pp. 509–520. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  5. 5.
    Olson, T.: Stereopsis for verging systems. In: CVPR 1993, pp. 55–60 (1993)Google Scholar
  6. 6.
    Scharstein, D., Szeliski, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision 47, 7–42 (2002)CrossRefzbMATHGoogle Scholar
  7. 7.
    Bouguet, J.Y.: Camera calibration toolbox for Matlab (1999)Google Scholar
  8. 8.
    Woods, A., Docherty, T., Koch, R.: Image distortions in stereoscopic video systems. In: Proceedings of the SPIE: Stereoscopic Displays and Applications IV, vol. 1915 (1993)Google Scholar
  9. 9.
    Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press (2004)Google Scholar
  10. 10.
    Gimel’farb, G.L.: Probabilistic regularisation and symmetry in binocular dynamic programming stereo. Pattern Recognition Letters 23, 431–442 (2002)CrossRefzbMATHGoogle Scholar
  11. 11.
    Jawed, K., Morris, J., Khan, T., Gimel’farb, G.: Real time rectification for stereo correspondence. In: Xue, J., Ma, J. (eds.) 7th IEEE/IFIP Intl Conf on Embedded and Ubiquitous Computing (EUC 2009), pp. 277–284. IEEE CS Press (2009)Google Scholar
  12. 12.
    Bradski, G., Kaehler, A.: Learning OpenCV: Computer vision with the OpenCV library. O’Reilly Media, Inc. (2008)Google Scholar
  13. 13.
    United States Bowling Congress: Equipment Specifications and Certification Manual (2009)Google Scholar
  14. 14.
    Khan, T., Morris, J., Javed, K., Gimelfarb, G.: Salmon: Precise 3d contours in real time. In: Proceedings of the 2009 Eighth IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2009, pp. 424–429. IEEE Computer Society, Washington, DC, USA (2009)CrossRefGoogle Scholar
  15. 15.
    Morris, J., Jawed, K., Gimel’farb, G., Khan, T.: Breaking the ’ton’: Achieving 1% depth accuracy from stereo in real time. In: Bailey, D. (ed.) Image and Vision Computing. IEEE CS Press, NZ (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Khurram Jawed
    • 1
  • John Morris
    • 1
  1. 1.Electrical and Computer EngineeringThe University of AucklandNew Zealand

Personalised recommendations