OSA's Digital Library

Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 7, Iss. 12 — Dec. 19, 2012

Experimental study of the influence of refraction on underwater three-dimensional reconstruction using the SVP camera model

Lai Kang, Lingda Wu, and Yee-Hong Yang  »View Author Affiliations


Applied Optics, Vol. 51, Issue 31, pp. 7591-7603 (2012)
http://dx.doi.org/10.1364/AO.51.007591


View Full Text Article

Enhanced HTML    Acrobat PDF (2258 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

In an underwater imaging system, a perspective camera is often placed outside a tank or in waterproof housing with a flat glass window. The refraction of light occurs when a light ray passes through the water–glass and air–glass interface, rendering the conventional multiple view geometry based on the single viewpoint (SVP) camera model invalid. While most recent underwater vision studies mainly focus on the challenging topic of calibrating such systems, no previous work has systematically studied the influence of refraction on underwater three-dimensional (3D) reconstruction. This paper demonstrates the possibility of using the SVP camera model in underwater 3D reconstruction through theoretical analysis of refractive distortion and simulations. Then, the performance of the SVP camera model in multiview underwater 3D reconstruction is quantitatively evaluated. The experimental results reveal a rather surprising and useful yet overlooked fact that the SVP camera model with radial distortion correction and focal length adjustment can compensate for refraction and achieve high accuracy in multiview underwater 3D reconstruction (within 0.7 mm for an object of dimension 200 mm) compared with the results of land-based systems. Such an observation justifies the use of the SVP camera model in underwater application for reconstructing reliable 3D scenes. Our results can be used to guide the selection of system parameters in the design of an underwater 3D imaging setup.

© 2012 Optical Society of America

OCIS Codes
(010.7340) Atmospheric and oceanic optics : Water
(330.1400) Vision, color, and visual optics : Vision - binocular and stereopsis

ToC Category:
Atmospheric and Oceanic Optics

History
Original Manuscript: July 6, 2012
Revised Manuscript: September 26, 2012
Manuscript Accepted: September 26, 2012
Published: October 26, 2012

Virtual Issues
Vol. 7, Iss. 12 Virtual Journal for Biomedical Optics

Citation
Lai Kang, Lingda Wu, and Yee-Hong Yang, "Experimental study of the influence of refraction on underwater three-dimensional reconstruction using the SVP camera model," Appl. Opt. 51, 7591-7603 (2012)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=ao-51-31-7591


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, 2nd ed. (Cambridge University, 2004).
  2. N. Snavely, S. M. Seitz, and R. Szeliski, “Modeling the world from internet photo collections,” Int. J. Comput. Vis. 80, 189–210 (2008). [CrossRef]
  3. V. Chari and P. Sturm, “Multiple-view geometry of the refractive plane,” in Proceedings of British Machine Vision Conference (BMVA, 2009).
  4. Y. Chang and T. Chen, “Multi-view 3D reconstruction for scenes under the refractive plane with known vertical direction,” in Proceedings of International Conference on Computer Vision (IEEE, 2011).
  5. P. C. Y. Chang, J. C. Flitton, K. I. Hopcraft, E. Jakeman, D. L. Jordan, and J. G. Walker, “Improving visibility depth in passive underwater imaging by use of polarization,” Appl. Opt. 42, 2794–2803 (2003). [CrossRef]
  6. W. Hou, S. Woods, E. Jarosz, W. Goode, and A. Weidemann, “Optical turbulence on underwater image degradation in natural environments,” Appl. Opt. 51, 2678–2686 (2012). [CrossRef]
  7. T. Treibitz, Y. Y. Schechner, C. Kunz, and H. Singh, “Flat refractive geometry,” IEEE Trans. Pattern Anal. Mach. Intell. 34, 51–65 (2012).
  8. P. Sturm and J. P. Barreto, “General imaging geometry for central catadioptric cameras,” in Proceedings of European Conference on Computer Vision (Springer, 2008), pp. 609–622.
  9. Z. Kukelova, M. Bujnak, and T. Pajdla, “Closed-form solutions to minimal absolute pose problems with known vertical direction,” in Proceedings of Asian Conference on Computer Vision (Springer, 2010), pp. 216–229.
  10. A. Sedlazeck and R. Koch, “Calibration of housing parameters for underwater stereo-camera rigs,” in Proceedings of British Machine Vision Conference (BMVA, 2011), paper 118.
  11. G. Telem and S. Filin, “Photogrammetric modeling of underwater environments,” ISPRS J. Photogramm. Remote Sens. 65, 433–444 (2010).
  12. A. Agrawal, S. Ramalingam, Y. Taguchi, and V. Chari, “A theory of multi-layer flat refractive geometry,” in IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2012), pp. 3346–3353.
  13. S. Ramalingam, P. Sturm, and S. K. Lodha, “Theory and calibration algorithms for axial cameras,” in Proceedings of Asian Conference on Computer Vision (Springer, 2006), pp. 704–713.
  14. R. Swaminathan, M. D. Grossberg, and S. K. Nayar, “A perspective on distortions,” in IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2003), pp. 594–601.
  15. Y. Swirski, Y. Y. Schechner, B. Herzberg, and S. Negahdaripour, “CauStereo: range from light in nature,” Appl. Opt. 50, F89–F101 (2011). [CrossRef]
  16. L. Bartolini, L. De Dominicis, M. Ferri de Collibus, G. Fornetti, M. Guarneri, E. Paglia, C. Poggi, and R. Ricci, “Underwater three-dimensional imaging with an amplitude-modulated laser radar at a 405 nm wavelength,” Appl. Opt. 44, 7130–7135 (2005). [CrossRef]
  17. C. Kunz and H. Singh, “Hemispherical refraction and camera calibration in underwater vision,” in Proceedings of MTS/IEEE Oceans (IEEE, 2008), pp. 1–7.
  18. S. M. Seitz, B. Curless, J. Diebel, D. Scharstein, and R. Szeliski, “A comparison and evaluation of multi-view stereo reconstruction algorithms,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2006), pp. 519–528.
  19. G. Glaeser and H.-P. Schrocker, “Reflections on refractions,” J. Geom. Graph. 4, 1–18 (2000).
  20. B. Triggs, P. F. Mclauchlan, R. I. Hartley, and A. W. Fitzgibbon, “Bundle adjustment—a modern synthesis,” in Proceedings of the International Workshop on Vision Algorithms: Theory and Practice (Springer, 1999), pp. 153–177.
  21. http://www.povray.org .
  22. http://graphics.stanford.edu/data .
  23. Y. Furukawa and J. Ponce, “Accurate, dense, and robust multiview stereopsis,” IEEE Trans. Pattern Anal. Mach. Intell. 32, 1362–1376 (2010).
  24. C. Strecha, W. von Hansen, L. Van Gool, P. Fua, and U. Thoennessen, “On benchmarking camera calibration and multi-view stereo for high resolution imagery,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2008), pp. 1–8.
  25. P. J. Besl and N. D. McKay, “A method for registration of 3-D shapes,” IEEE Trans. Pattern Anal. Mach. Intell. 14, 239–256 (1992).
  26. D. G. Lowe, “Distinctive image features from scale-invariant keypoints,” Int. J. Comput. Vis. 60, 91–110 (2004).
  27. M. Muja and D. G. Lowe, “Fast approximate nearest neighbors with automatic algorithm configuration,” in Proceedings of International Conference on Computer Vision Theory and Applications (INSTICC, 2009).
  28. B. K. P. Horn, “Closed-form solution of absolute orientation using unit quaternions,” J. Opt. Soc. Am. A 4, 629–642 (1987). [CrossRef]
  29. D. S. D. Chetverikov, D. Svirko, and P. Krsek, “The trimmed iterative closest point algorithm,” in Proceedings of International Conference on Pattern Recognition(IEEE, 2002), Vol. 3, pp. 545–548.

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited