Skip to main content
SpringerLink
Log in

Camera calibration using identical objects

  • Original Paper
  • Published:
Machine Vision and Applications Aims and scope Submit manuscript

Abstract

This paper describes a method for camera calibration using identical products. In this paper, we postulate an imaginative rigid motion between any two identical products, and the imaginative rigid motion could offer a pair of circular points. As is known, three pairs of projections of the circular points are needed to result in the closed-form solution for calibration. In our method, we obtain three pairs of projections of the circular points from only two images of three identical products, or three images of two identical products. When only two identical products are utilized, our method is almost the dual of the stereo calibration from rigid motions. A direct approach is taken here instead of the two-step process in stereo calibration. Furthermore, a better projective reconstruction could be performed from the estimation of the camera parameters to avoid the dominant projective-to-affine error in the stereo calibration. Finally, we conduct a nonlinear refinement based on the maximum likelihood estimation. The experimental results from synthetic data and real data prove our method convenient and robust to noise.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Armstrong, M.N.: Self-Calibration from Image Sequences. Ph.D. Thesis, University of Oxford (1996)

  2. Canny J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8(6), 679–698 (1986)

    Article  Google Scholar 

  3. Cao X., Foroosh H.: Camera calibration using symmetric objects. IEEE Trans. Image Process 15(11), 3614–3619 (2006)

    Article  Google Scholar 

  4. Cho, M., Shin, Y.M., Lee, K.M.: Unsupervised detection and segmentation of identical objects. In: IEEE Conference of Computer Vision Pattern Recognition (2010)

  5. Csurka G., Demirdjian D., Horaud R.: Finding the collineation between two projective reconstructions. Comput. Vis. Image Underst. 75(3), 260–268 (1999)

    Article  Google Scholar 

  6. Devernay, F., Faugeras, O.: From projective to euclidean reconstruction. In: Computer Vision and Pattern Recognition Conference, pp. 264–269 (1996)

  7. Faugeras O.: Three-dimensional Computer Vision: a Geometric Viewpoint. MIT Press, Cambridge (1993)

    Google Scholar 

  8. Faugeras O., Maybank S.: Motion from point matches: multiplicity of solutions. Int. J. Comput. Vis. 4, 225–246 (1990)

    Article  Google Scholar 

  9. Hartley R., Zisserman A.: Multiple View Geometry in Computer Vision. Cambridge University Press, London (2000)

    MATH  Google Scholar 

  10. Heikkilä J.: Geometric camera calibration using circular control points. IEEE Trans. Pattern Anal. Mach. Intell. 22(10), 1066–1077 (2000)

    Article  Google Scholar 

  11. Longuet-Higgins H.C.: A computer algorithm for reconstructing a scene from two projections. Nature 293(10), 133–135 (1981)

    Article  Google Scholar 

  12. Horaud R., Demirdijian D.: Stereo calibration from rigid motions. IEEE Trans. Pattern Anal. Mach. Intell. 22(12), 1446–1452 (2000)

    Article  Google Scholar 

  13. Horn, B.K.P.: Recovering baseline and orientation from essential matrix. J. Opt. Soc. Am. (1990)

  14. Jiang, G., Quan, L.: Detection of concentric circles for camera calibration. In: International Conference on Computer Vision, pp. 333–340 (2005)

  15. Jiang G., Quan L., Tsui H.-T.: Circular motion geometry using minimal data. IEEE Trans. Pattern Anal. Mach. Intell. 26(6), 721–731 (2004)

    Article  Google Scholar 

  16. Lhuillier, M., Quan, L.: Robust dense matching using local and global geometric constraints. In: International Conference on Pattern Recognition, pp. 1968–1972 (2000)

  17. Lowe D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)

    Article  Google Scholar 

  18. More, J.: The levenberg-marquardt algorithm, implementation and theory. In: Watson, G.A. Numerical Analysis. Lecture Notes in Mathematics, vol. 630. Springer, Berlin (1977)

  19. Quan L.: Image-based Modeling. Springer, Berlin (2010)

    Book  MATH  Google Scholar 

  20. Semple J., Kneebone G.: Algebraic Projective Geometry. Oxford University Press, NY (1952)

    MATH  Google Scholar 

  21. Shashua A.: Projecitve structure form uncalibrated images: structure from motion and recognition. IEEE Trans. Pattern Anal. Mach. Intell. 16(8), 778–790 (1994)

    Article  Google Scholar 

  22. Sturm, P.: On Focal length calibration from two views. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 145–150 (2001)

  23. Tsai R.Y.: A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf tv cameras and lenses. IEEE J. Robot. Autom. 3(4), 323–344 (1987)

    Article  Google Scholar 

  24. Zhang Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)

    Article  Google Scholar 

  25. Zhang Z.: Camera calibration with one-dimensional objects. IEEE Trans. Pattern Anal. Mach. Intell. 26(7), 892–898 (2004)

    Article  Google Scholar 

  26. Zhang C., Guo X., Cao X.: Duplication localization and segmentation. PCM 2010, Part I, LNCS 6297, pp. 578–589. Springer, Berlin (2010)

    Google Scholar 

  27. Zisserman, A., Beardsley, P.A., Reid, I.D.: Metric Calibration of a Stereo Rig. In: Proceedings of IEEE Workshop Representation of Visual Scenes, pp. 93–100 (1995)

Download references

Author information

Authors and Affiliations

  1. State Key Laboratory of Integrated Service Networks, School of Telecommunications Engineering, Xidian University, Xi′an, 710071, Shaanxi, People’s Republic of China

    Ruiyan Wang, Guang Jiang & Chengke Wu

  2. Hong Kong University of Science and Technology, Hong Kong, People’s Republic of China

    Long Quan

Authors
  1. Ruiyan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guang Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Long Quan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chengke Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ruiyan Wang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wang, R., Jiang, G., Quan, L. et al. Camera calibration using identical objects. Machine Vision and Applications 23, 579–587 (2012). https://doi.org/10.1007/s00138-010-0316-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00138-010-0316-6

Keywords

Search

Navigation