Advertisement

Two Linear Methods for Camera Calibration and Their Applications to Augmented Reality and 3D Reconstruction

  • Jang-Hwan Im
  • Ji-Hong Min
  • Hyung-Soo Ohk
  • Jong-Soo Choi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)

Abstract

This paper presents two new compact camera calibration methods: one is derived from a calibration pattern that consists of two planes orthogonal to each other; the other is derived from a calibration pattern that consists of three planar patterns which need not to be orthogonal. In particular, these methods allow to vary the intrinsic parameters of a camera. In order to demonstrate the effectiveness of the proposed methods, two camera calibration methods are applied to an augmented reality system with a moving zoom lens camera and a 3D reconstruction system respectively. Two applications have shown that the proposed methods are reliable.

References

  1. [1]
    R. T. Azuma and G. Bishop, “Improving static and dynamic registration in an optical see through display”, In Proc. SIGGRAPH’94, pages 194–204.Google Scholar
  2. [2]
    B. Caprile and V. Torre, “Using Vanishing Points for Camera Calibration,” The International Journal of Computer Vision, 4(2): 127–140, 1990.CrossRefGoogle Scholar
  3. [3]
    G. Golub and C. van Loan, Matrix Computations, The John Hopkins University, Baltimore, Maryland, 3 edition, 1996.zbMATHGoogle Scholar
  4. [4]
    R. Hartely and A. Zissermann, Multiple View Geometry in Computer Vision, Cambridge University Press, 2000.Google Scholar
  5. [5]
    G. Simon and M.-O. Berger, “A Two-stage Robust Statistical Method for Temporal Registration from Features of Various Type”, In Proc. ICCV’98, pages 261–266.Google Scholar
  6. [6]
    B. Triggs, “Auto-calibration and the absolute quadric”, In Proc. IEEE Conference on Computer Vision and Pattern Recognition, pages 609–614, 1997.Google Scholar
  7. [7]
    R. Y. Tsai, “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, 3(4):323–344, 1987.CrossRefGoogle Scholar
  8. [8]
    M. Uenohara and T. Kanade, “Vision based object registration for real time image overlay”, Journal of Computers in Biology and Medecine, 1996.Google Scholar
  9. [9]
    Z. Zhang, “A flexible new technique for camera calibration”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(11):1330–1334, 2000.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Jang-Hwan Im
    • 1
  • Ji-Hong Min
    • 1
  • Hyung-Soo Ohk
    • 1
  • Jong-Soo Choi
    • 1
  1. 1.Image Engineering Graduate School of Advanced Imaging ScienceMultimedia, and Film Chung-Ang UniversitySeoulKorea

Personalised recommendations