Object pose by affine iterations

  • Fadi Dornaika
  • Christophe Garcia
Poster Session B: Active Vision, Motion, Shape, Stereo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1310)


The problem of a real-time pose estimation between a 3D scene and a camera is a fundamental task in most 3D computer vision and robotics applications such as object tracking, visual servoing, and virtual reality. In this paper we present a fast method for estimating the 3D pose using 2D to 3D point and line correspondences. This method is inspired by DeMenthon's method (1995) which consists of determining the pose from point correspondences. In this method the pose is iteratively improved with a weak perspective camera model, at convergence the computed pose corresponds to the perspective camera model. Our method is based on the iterative use of a paraperspective camera model which is a first order approximation of perspective. Experiments involving synthetic data as well as real range data indicate the feasibility and robustness of this method.


  1. 1.
    D. DeMenthon and L. Davis. Model-based object pose in 25 lines of code. International Journal of Computer Vision, 15:123–141, June 1995.Google Scholar
  2. 2.
    M. Dhome, M. Richetin, J.T. Lapreste, and G. Rives. Determinition of the attitude of 3d objects from a single perspective view. IEEE Trans. on Pattern Analysis and Machine Intelligence, 11(12):1265–1278, 1989.Google Scholar
  3. 3.
    B. Espiau, F. Chaumette, and P. Rives. A new approach to visual servoing in robotics. IEEE Transactions on Robotics and Automation, 8(3):313–326, June 1992.Google Scholar
  4. 4.
    N. Hollinghurst and R. Cipolla. Uncalibrated stereo hand-eye coordination. In Proceedings of the Fourth British Machine vision Conference (BMVC 93), 1993.Google Scholar
  5. 5.
    R. Horaud, B. Conio, O. Leboulleux, and B. Lacolle. An analytic solution for the perspective 4-point problem. Computer Vision, Graphics, and Image Processing, 47(1):33–44, July 1989.Google Scholar
  6. 6.
    Y. Ohta, K. Maenobu, and T. Sakai. Obtaining surface orientation from texels under perspective projection. In Proceedings of the 7th IJCAI, 1981.Google Scholar
  7. 7.
    J. Yuan. A general photogrammetric method for determining object position and orientation. IEEE Transactions on Robotics and Automation, 5(2):129–142, 1989.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Fadi Dornaika
    • 1
  • Christophe Garcia
    • 1
  1. 1.GMD - German National Research Center for Information TechnologyInstitute For System Design TechnologySankt AugustinGermany

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