Skip to main content
SpringerLink
Log in

Affine Camera for 3-D Retinal Surface Reconstruction

  • Conference paper
Advances in Visual Computing (ISVC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4292))

Included in the following conference series:

Abstract

We study 3D retinal surface reconstruction by using an affine camera due to two following reasons: (1) NIH’s retinal imaging protocols specify a narrow field of view and (2) each retinal image has small depth variation. Specifically, we incorporate the prior knowledge of human retina geometry in the reconstruction process, and introduce a point-based approach to estimate the retinal spherical surface. We also show that lens distortion removal and affine bundle adjustment improve the reconstruction error in terms of the deviation from the underling spherical surface. Simulation results on both synthetic data and real images show the effectiveness and robustness of the proposed algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Deguchi, K., Kawamata, D., Mizutani, K., Hontani, H., Wakabayashi, K.: 3d fundus shape reconstruction and display from stereo fundus images. IEICE Trans. Inf. & Syst. E83-D, 1408–1414 (2000)

    Google Scholar 

  2. Deguchi, K., Noami, J., Hontani, H.: 3d fundus pattern reconstruction and display from multiple images. In: IEEE Int’l conference on Pattern Recognition, vol. 4, pp. 94–97 (2000)

    Google Scholar 

  3. Choe, T., Cohen, I., Medioni, G.: 3-d shape reconstruction of retinal fundus. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 2277–2284 (2006)

    Google Scholar 

  4. Chanwimaluang, T., Fan, G.: Hybrid retinal image registration. IEEE Trans. Information Technology in Biomedicine 10, 129–142 (2006)

    Article  Google Scholar 

  5. Zhang, Z.: Flexible camera calibration by viewing a plane from unknown orientations. In: IEEE Int’l Conference on Computer Vision, vol. 1, pp. 666–673 (1999)

    Google Scholar 

  6. Koenderink, J.J., Van Doorn, A.J.: Affine structure from motion. Journal of Optical Society of America 8, 377–385 (1991)

    Article  Google Scholar 

  7. Quan, L., Mohr, R.: Towards structure from motion for linear features through reference points. In: IEEE Workshop on Visual Motion, pp. 249–254 (1991)

    Google Scholar 

  8. Demey, S., Zisserman, A., Beardsley, P.: Affine and projective structure from motion. In: Proc. British Machine Vision Conference (BMVC), pp. 49–58 (1992)

    Google Scholar 

  9. Shapiro, L.S.: Affine Analysis of Image Sequences. PhD thesis, Sharp Laboratories of Europe, Oxford, UK (1995)

    Google Scholar 

  10. Tomasi, C., Kanade, T.: Shape and motion from image streams under orthography: A factorization method. Intl. Journal of Computer Vision 9, 137–154 (1992)

    Article  Google Scholar 

  11. Triggs, B., McLauchlan, P., Hartley, R., Fitzgibbon, A.: Bundle adjustment: A modern synthesis. In: Vision Algorithms: Theory And Practice. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  12. Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2003)

    Google Scholar 

  13. Tresadern, P., Reid, I.: Uncalibrated and unsynchronized human motion capture: a stereo factorization approach. In: IEEE Conference on Computer Vision and Pattern Recognition CVPR, vol. 1, pp. 128–134 (2004)

    Google Scholar 

  14. Weinshall, D., Tomasi, C.: Linear and incremental acquisition of invariant shape models from image sequences. In: IEEE Proc. of 4th Int’l Conference on Computer Vision, vol. 17, pp. 512–517 (1993)

    Google Scholar 

  15. Weinshall, D., Tomasi, C.: Linear and incremental acquisition of invariant shape models from image sequences. IEEE Trans. pattern Anal. Machine Intell. PAMI 17, 512–517 (1995)

    Article  Google Scholar 

  16. Poleman, C.J., Kanade, T.: A paraperspective factorization method for shape and motion recovery. In: Proc. of 3rd European Conference on Computer Vision, pp. 97–108 (1994)

    Google Scholar 

  17. Poleman, C.J., Kanade, T.: A paraperspective factorization method for shape and motion recovery. IEEE Trans. Pattern and Machine Intelligent 19, 206–218 (1997)

    Article  Google Scholar 

  18. Quan, L.: Self-calibration of an affine camera from multiple views. International Journal of Computer Vision 19, 93–110 (1996)

    Article  Google Scholar 

  19. Kurata, T., Fujiki, J., Sakaue, K.: Affine epipolar geometry via factorization method. In: Proc. of 14th Int’l Conference on Pattern Recognition, vol. 1, pp. 862–866 (1998)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK, 74078, USA

    Thitiporn Chanwimaluang & Guoliang Fan

Authors
  1. Thitiporn Chanwimaluang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guoliang Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Digital Image Research Center, Kingston University, London, UK

    Paolo Remagnino

  6. Intel, 95052, Santa Clara, CA, USA

    Ara Nefian

  7. University of California, 430, Computer Science Building, 92697-3425, Irvine, CA, USA

    Gopi Meenakshisundaram

  8. Institute for Data Analysis and Visualization, P.O. Box

    Valerio Pascucci

  9. Department of Computer Science and Engineering, Czech Technical University in Prague, Czech

    Jiri Zara

  10. Rockwell Scientific, 1049 Camino Dos Rios, 91360, Thousand Oaks, CA, USA

    Jose Molineros

  11. Computer Graphics Group, Bielefeld University, D-33501, Bielefeld, Germany

    Holger Theisel

  12. Hewlett Packard Labs, Palo Alto, CA, USA

    Tom Malzbender

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chanwimaluang, T., Fan, G. (2006). Affine Camera for 3-D Retinal Surface Reconstruction. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2006. Lecture Notes in Computer Science, vol 4292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11919629_3

Download citation

  • DOI: https://doi.org/10.1007/11919629_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-48626-8

  • Online ISBN: 978-3-540-48627-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation