International Journal of Computer Vision

, Volume 48, Issue 3, pp 195–214

A Pupil-Centric Model of Image Formation

  • Manoj Aggarwal
  • Narendra Ahuja
Article

Abstract

This paper has been prompted by observations of some anomalies in the performance of the standard imaging models (pin-hole, thin-lens and Gaussian thick-lens), in the context of composing omnifocus images and estimating depth maps from a sequence of images. A closer examination of the models revealed that they assume a position of the aperture that conflicts with the designs of many available lenses. We have shown in this paper that the imaging geometry and photometric properties of an image are significantly influenced by the position of the aperture. This is confirmed by the discrepancies between observed mappings and those predicted by the models. We have therefore concluded that the current imaging models do not adequately represent practical imaging systems. We have proposed a pupil-centric model of image formation, which overcomes these deficiencies and have given the associated mappings. The impact of this model on some common imaging scenariosis described, along with experimental verification of the better performance of the model on three real lenses.

image model pin-hole thin-lens Gaussian thick-lens aperture position camera design depth from (de)focus entrance end exit pupils 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aggarwal, M. and Ahuja, N. 2000. Camera center estimation. In International Conference on Pattern Recognition, pp. 876–880.Google Scholar
  2. Aggarwal, M., Hua, H., and Ahuja, N. 2001. On cosine-fourth and vignetting effects in real lenses. In International Conference on Computer Vision, Vol. 2., pp. 472–479.Google Scholar
  3. Castano, A. 1998. Range from non-frontal imaging camera. Ph.D. Thesis, University of Illinois at Urbana-Champaign.Google Scholar
  4. Faugeras, O.D. 1995. Stratification of the three-dimensional vision: Projective, affine, and metric representations. Journal of Optical Society of America A., 12(3): 465–484.Google Scholar
  5. Forsyth, D. and Ponce, J. 2000. Computer Vision-A Modern Approach. In preparation, draft 3, www.cs.berkeley.edu/ daf.Google Scholar
  6. Hecht, E. and Zajac, A. 1974. Optics. Addison Wesley: Reading, MA.Google Scholar
  7. Horn, B.K.P. 1986. Robot Vision. The MIT Press: Cambridge, Mass.Google Scholar
  8. Kingslake, R. 1978. Lens Design Fundamantals. Academic Press: San Mateo, CA.Google Scholar
  9. Kingslake, R. 1983. Optical System Design. Academic Press: San Mateo, CA.Google Scholar
  10. Kolb, C., Mitchell, D., and Hanrahan, P. 1995. A realistic camera model for computer graphics. In Proceedings of SIGGGRAPH, pp. 317–324.Google Scholar
  11. Krishnan, A. 1997. Non-frontal imaging camera. Ph.D. Thesis, University of Illinois at Urbana-Champaign.Google Scholar
  12. Krishnan, A. and Ahuja, N. 1996. Range estimation from focus using a non-frontal imaging camera. International Journal of Computer Vision, 20(3): 169–185.Google Scholar
  13. Smith, W.J. 1992. Modern Lens Design-A Resource Manual. McGraw Hill: New York.Google Scholar
  14. Triggs, B. 1998. Autocalibration from planar scenes. In European Conference on Computer Vision, Vol. 1., pp. 89–105.Google Scholar
  15. Tsai, R.R. 1986. An efficient and accurate camera calibration tech-nique for 3D machine vision. In Conference on Computer Vision and Pattern Recognition, pp. 364–374.Google Scholar
  16. Tsai, R.Y. 1987. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the shelf TV cameras and lenses. IEEE Journal of Robotics and Automation, RA-3(4): 323–344.Google Scholar
  17. Watanabe, M. and Nayar, S.K. 1997. Telecentric optics for focus analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(12): 1360–1365.Google Scholar
  18. Zhang, Z. 2000. A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(11): 1330–1334.Google Scholar

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Manoj Aggarwal
    • 1
  • Narendra Ahuja
    • 2
  1. 1.Sarnoff CorporationPrincetonUSA
  2. 2.University of Illinois at Urbana-ChampaignUrbanaUSA

Personalised recommendations