Skip to main content
SpringerLink
Log in

Indirect Tracking to Reduce Occlusion Problems

  • Conference paper
Advances in Visual Computing (ISVC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5359))

Included in the following conference series:

Abstract

There exist many infrared inside-out 6-DOF pose tracking configurations with cameras mounted rigidly to the environment. In such a setup, tracking is inherently impossible for IR targets inside/below/behind other opaque objects (occlusion problem).

We present a solution for the integration of an additional, mobile IR tracking system to overcome this problem. The solution consists of an indirect tracking setup where the stationary cameras track the mobile cameras which in turn track the target. Accuracy problems that are inherent to such an indirect tracking setup, are tackled by an error correction mechanism based on reference points in the scene that are known to both tracking systems. An evaluation demonstrates that, in naive indirect tracking without error correction, the major source of error consists in a wrong detection of orientation of the mobile system and that this source of error can be practically eliminated by our error correction mechanisms.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bauer, M., Schlegel, M., Pustka, D., Navab, N., Klinker, G.: Predicting and estimating the accuracy of vision-based optical tracking systems. In: Proc. IEEE International Symposium on Mixed and Augmented Reality (ISMAR 2006), Santa Barbara, CA, USA (October 2006)

    Google Scholar 

  2. Bichlmeier, C., Sielhorst, T., Navab, N.: The tangible virtual mirror: New visualization paradigm for navigated surgery. In: AMIARCS - The Tangible Virtual Mirror: New Visualization Paradigm for Navigated Surgery, Copenhagen, Denmark, October 2006, MICCAI Society (2006)

    Google Scholar 

  3. Eggert, D., Lorusso, A., Fisher, R.: Estimating 3-d rigid body transformations: a comparison of four major algorithms. Machine Vision and Applications 9(5), 272–290 (1997)

    Article  Google Scholar 

  4. Fischer, J., Neff, M., Freudenstein, D., Bartz, D.: Medical Augmented Reality based on Commercial Image Guided Surgery. In: Proceedings of Eurographics Symposium on Virtual Environments (EGVE), pp. 83–86 (2004)

    Google Scholar 

  5. Fua, P., Lepetit, V.: Emerging Technologies of Augmented Reality, Interfaces and Design, chapter Vision. In: Based 3D Tracking and Pose Estimation for Mixed Reality, pp. 1–22. Idea Group Publishing (2007)

    Google Scholar 

  6. Hartley, R., Zisserman, A.: Multiple View Geometry in computer vision. Cambridge University Press, Cambridge (2000)

    MATH  Google Scholar 

  7. Hoff, W., Vincent, T.: Analysis of head pose accuracy in augmented reality. In: IEEE Transactions on Visualization and Computer Graphics, vol. 6, pp. 319–334. IEEE Computer Society, Los Alamitos (2000)

    Google Scholar 

  8. Horn, B.K.P.: Closed-form solution of absolute orientation using unit quaternions. Journal of the Optical Society of America 4(4) (April 1987)

    Google Scholar 

  9. Huber, M., Pustka, D., Keitler, P., Echtler, F., Klinker, G.: A system architecture for ubiquitous tracking environments. In: Proceedings of the 6th International Symposium on Mixed and Augmented Reality (ISMAR) (November 2007)

    Google Scholar 

  10. Kalman, R.: A new approach to linear filtering and prediction problems. Journal of Basic Engineering 82(1), 35–45 (1960)

    Article  Google Scholar 

  11. Mulder, A.: Human movement tracking technology. Technical Report 94-1, School of Kinesiology, Simon Fraser University, Burnaby, B.C., Canada (1994)

    Google Scholar 

  12. Nölle, S.: Augmented Reality als Vergleichswerkzeug am Beispiel der Automobilindustrie. PhD thesis, Technische Universität München (2006)

    Google Scholar 

  13. Pustka, D., Keitler, P., Huber, M., Echtler, F., Klinker, G.: Ubiquitous tracking for quickly solving multi-sensor calibration and tracking problems. In: Demonstration at IEEE International Symposium on Mixed and Augmented Reality (ISMAR 2007) (November 2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Fakultät für Informatik, Technische Universität München, Boltzmannstraße 3, 85748, Garching b. München, Germany

    Peter Keitler, Michael Schlegel & Gudrun Klinker

Authors
  1. Peter Keitler
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael Schlegel
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gudrun Klinker
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Digital Image Research Center, Kingston University, London, UK

    Paolo Remagnino

  6. Mitsubishi Electric Research Laboratories, P.O. Box 02139, Cambridge, MA, USA

    Fatih Porikli

  7. Computer and Information Science and Engineering, University of Florida, P.O. Box, FL 32611-6120, Gainsville, USA

    Jörg Peters

  8. IBM T.J. Watson Research Center, 19 Skyline Drive, NY 10532, Hawthorne, USA

    James Klosowski

  9. 128 Memorial Mall, Stewart B001, IN 47907, West Lafayette, USA

    Laura Arns

  10. Denver Museum of Nature and Space, 2001 Colorade Blvd. Denver,, CO 80205, USA

    Yu Ka Chun

  11. Departmen of Computer Science,, NC State University, Campus Box 8206, NC 27695-8206, Raleigh, USA

    Theresa-Marie Rhyne

  12. Los Alamos National Labs, P.O. Box 1663, NM 87545, Los Alamos, USA

    Laura Monroe

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Keitler, P., Schlegel, M., Klinker, G. (2008). Indirect Tracking to Reduce Occlusion Problems. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89646-3_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-89646-3_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89645-6

  • Online ISBN: 978-3-540-89646-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation