Skip to main content

A feature map approach to pose estimation based on quaternions

  • Part VI: Speech, Vision, and Pattern Recognition
  • Conference paper
  • First Online:
Artificial Neural Networks — ICANN'97 (ICANN 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1327))

Included in the following conference series:

Abstract

This paper proposes a novel solution to the problem of pose estimation of three-dimensional objects using feature maps. Our approach relies on quaternions as the mathematical representation of object orientation. We introduce the rigid map, which is derived from Kohonen's self-organizing feature map. Its topology is fixed and chosen in accordance with the quaternion representation. The map is trained with computer-generated object views such that it responds to a preprocessed input image with one or more sets of object orientation parameters. Experimental results demonstrate that a pose estimate within the accuracy requirements can be found in more than 90% of all cases. Our current implementation operates at near frame rate on real input images.

now with the Signal Processing Lab of the Swiss Federal Institute of Technology in Lausanne, Switzerland

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. H. S. M. Coxeter: Regular Polytopes. Dover, 1973.

    Google Scholar 

  2. W. R. Hamilton: Elements of Quaternions. Chelsea, 1969.

    Google Scholar 

  3. A. Khotanzad, J. Liou: “Recognition and pose estimation of 3-D objects from a single 2-D perspective view by banks of neural networks.” in Proc. Artifical Neural Networks in Engineering Conference, pp. 479–484, ASME Press, 1991.

    Google Scholar 

  4. D. G. Lowe: “Fitting parametrized three-dimensional models to images.” in IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 60, no. 5, pp. 441–450, May 1991.

    Google Scholar 

  5. M.-C. Lu, C.-H. Lo, H.-S. Don: “A neural network approach to 3-D object identification and pose estimation.” in Proc. Int. Conf. on Artificial Neural Networks, pp. 2600–2605, 1991.

    Google Scholar 

  6. C. Maggioni, B. Wirtz: “A neural net approach to 3-D pose estimation.” in Proc. Int. Conf. on Artificial Neural Networks, pp. 75–80, 1991.

    Google Scholar 

  7. K. Park, D. J. Cannon: “Recognition and localization of a 3-D polyhedral object using a neural network.” in Proc. IEEE Int. Conf. on Robotics and Automation, pp. 3613–3618, 1996.

    Google Scholar 

  8. T. Poggio, S. Edelman: “A network that learns to recognize three-dimensional objects.” in Nature, vol. 343, pp. 263–266, 1991.

    Google Scholar 

  9. H. J. Ritter: “Learning with the self-organizing map.” in Proc. Int. Conf. on Artificial Neural Networks, pp. 379–384, 1991.

    Google Scholar 

  10. K. Shoemake: “Animating rotation with quaternion curves.” in Computer Graphics, vol. 19, no. 3, pp. 245–254, July 1985.

    Google Scholar 

  11. S. Winkler: Model-Based Pose Estimation of 3-D Objects from Camera Images Using Neural Networks. Technical Report 515-96-12, German Aerospace Research Establishment-DLR. Master's Thesis, TU Vienna, Austria, 1996.

    Google Scholar 

  12. P. Wunsch, G. Hirzinger: “Registration of CAD-models to images by iterative inverse perspective matching.” in Proc. Int. Conf. on Pattern Recognition, pp. 78–83, 1996.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Wulfram Gerstner Alain Germond Martin Hasler Jean-Daniel Nicoud

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Winkler, S., Wunsch, P., Hirzinger, G. (1997). A feature map approach to pose estimation based on quaternions. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020275

Download citation

  • DOI: https://doi.org/10.1007/BFb0020275

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63631-1

  • Online ISBN: 978-3-540-69620-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics