Correspondence-Free Multi Camera Calibration by Observing a Simple Reference Plane

  • Satoshi Kawabata
  • Yoshihiro Kawai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6494)


In the present paper, we propose a multi camera calibration method that estimates both the intrinsic and extrinsic parameters of each camera. Assuming a reference plane has an infinitely repeated pattern, finding corresponding points between cameras is regarded as being equivalent to the estimation of discrete 2-D transformation on the observed reference plane. This means that the proposed method does not require any overlap of the observed region, and bundle adjustment can be performed in the sense of point-to-point correspondence. Our experiment demonstrates that the proposed method is practically admissible and sufficiently useful for building a simple shape measurement system using multiple cameras.


Reference Plane Camera Calibration Intrinsic Parameter Bundle Adjustment Extrinsic Parameter 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Zhang, Z.: A flexible new technique for camera calibration. tPAMI 22, 1330–1334 (2000)CrossRefGoogle Scholar
  2. 2.
    Tsai, R.: A versatile camera calibration techniaue for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE J. Robot. and Autom. 3, 323–344 (1987)CrossRefGoogle Scholar
  3. 3.
    Pollefeys, M., Koch, R., Gool, L.V.: Self-calibration and metric reconstruction inspite of varying and unknown intrinsic camera parameters. IJCV 32, 7–25 (1999)CrossRefGoogle Scholar
  4. 4.
    Sturm, P.: Algorithms for plane-based pose estimation. In: Proc. CVPR 2000, Hilton Head Island, South Carolina, USA, pp. 1010–1017 (2000)Google Scholar
  5. 5.
    Caprile, B., Torre, V.: Using vanishing points for camera calibration. IJCV 4, 127–139 (1990)CrossRefGoogle Scholar
  6. 6.
    Ueshiba, T., Tomita, F.: Plane-based calibration algorithm for multi-camera systems via factorization of homography matrices. In: Proc. ICCV 2003, pp. 966–973 (2003)Google Scholar
  7. 7.
    Ramalingam, S., Sturm, P., Lodha, S.K.: Towards complete generic camera calibration. In: Proc. CVPR 2005, vol. 1, pp. 1093–1098 (2005)Google Scholar
  8. 8.
    Fiala, M.: ARTag, a fiducial marker system using digital techniques. In: Proc. CVPR 2005, vol. 2, pp. 590–596 (2005)Google Scholar
  9. 9.
    Lowe, D.: Object recognition from local scale-invariant features. In: Proc. ICCV 1999, pp. 1150–1157 (1999)Google Scholar
  10. 10.
    Horn, B.: Closed-form solution of absolute orientation using unit quaternions. J. the Optical Society of America A 4, 629–642 (1987)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Satoshi Kawabata
    • 1
  • Yoshihiro Kawai
    • 1
  1. 1.AIST Tsukuba Central 2National Institute of Advanced Industrial Science and Technology (AIST)IbarakiJapan

Personalised recommendations