A Rapidly Adaptive Collaborative Ubiquitous Computing Environment to Allow Passive Detection of Marked Objects

  • Hannah Slay
  • Bruce Thomas
  • Rudi Vernik
  • Wayne Piekarski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3101)


This paper presents a tool to support the rapid and adaptive deployment of a collaborative, ubiquitous computing environment. A key tool for the configuration and deployment of this environment is a calibration tool to quickly and efficiently calculate the positions of cameras in a dynamic environment. This tool has been incorporated into our current Passive Detection Framework. The paper describes the context where our rapidly adaptive collaborative ubiquitous computing environment would be deployed. The results of a study to test the accuracy of the calibration tool are also presented. This study found that the calibration tool can calculate the position of cameras to within 25 mm for all lighting conditions examined.


Augmented Reality Ubiquitous Computing Fiducial Marker Marked Object Ubiquitous Computing Environment 
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.


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  1. 1.
    Weiser, M.: The computer for the 21st century. Scientific American 265(3), 66–75 (1991)CrossRefGoogle Scholar
  2. 2.
    Slay, H., Vernik, R., Thomas, B.: Using ARToolkit for Passive Tracking and Presentation in Ubiquitous Workspaces. In: Second International IEEE ARToolkit Workshop, Waseda University, Japan (2003)Google Scholar
  3. 3.
    Slay, H., Thomas, B.: An Interaction Model for Universal Interaction and Control in Multi Display Environments. In: International Symposium on Information and Communication Technologies, Trinity College Dublin, Ireland (2003)Google Scholar
  4. 4.
    Slay, H., et al.: Interaction Modes for Augmented Reality Visualisation. In: Australian Symposium on Information Visualisation, Sydney, Australia (2001)Google Scholar
  5. 5.
    Kato, H., Billinghurst, M.: Marker Tracking and HMD Calibration for a Video-based Augmented Reality Conferencing System. In: 2nd IEEE and ACM International Workshop on Augmented Reality, San Francisco, USA (1999)Google Scholar
  6. 6.
    Streitz, N.A., Geißler, J., Holmer, T.: Roomware for Cooperative Buildings: Integrated De-sign of Architectural Spaces and Information Spaces. In: Streitz, N.A., Konomi, S., Burkhardt, H.-J. (eds.) CoBuild 1998. LNCS, vol. 1370, p. 4. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  7. 7.
    Grønbæk, K., Krogh, P.G., Kyng, M.: Intelligent Buildings and pervasive computing - research perspectives and discussions. In: Proc. of Conference on Architectural Research and In-formation Technology, Arhus (2001)Google Scholar
  8. 8.
    Brooks, R.A., et al.: The Intelligent Room Project. In: Second International Conference on Cognitive Technology Humanizing the Information Age, IEEE Computing Society, Los Alamitos (1997)Google Scholar
  9. 9.
    Johanson, B., Fox, A., Winograd, T.: The Interactive Workspaces Project: Experiences with Ubiquitous Computing Rooms. IEEE Pervasive Computing 1(2), 67–74 (2002)CrossRefGoogle Scholar
  10. 10.
    Morency, L.-P., et al.: Fast stereo-based head tracking for interactive environments. In: Proceedings Fifth IEEE International Conference on Automatic Face Gesture Recognition, May 20-21, IEEE, Washington (2002)Google Scholar
  11. 11.
    Pentland, A.: Looking at people: sensing for ubiquitous and wearable computing. IEEE Transac-tions on Pattern Analysis and Machine Intelligence 22(1), 107–119 (2000)CrossRefGoogle Scholar
  12. 12.
    Vernik, R., Blackburn, T., Bright, D.: Extending Interactive Intelligent Workspace Architectures with Enterprise Services. In: Evolve: Enterprise Information Integration, Sydney, Australia (2003)Google Scholar
  13. 13.
    Newman, J., Ingram, D., Hopper, A.: Augmented Reality in a Wide Area Sentient Environment. In: International Symposium on Augmented Reality, New York, USA (2001)Google Scholar
  14. 14.
    Piekarski, W., et al.: Hybrid Indoor and Outdoor Tracking for Mobile 3D Mixed Reality. In: The Second IEEE and ACM International Symposium on Mixed and Augmented Reality, Tokyo, Japan (2003)Google Scholar
  15. 15.
    Foxlin, E., Leonid, N.: VIS-Tracker: A Wearable Vision-Inertial Self-Tracker. IEEE Virtual Reality, Los Angeles, USA (2003)Google Scholar
  16. 16.
    Malbezin, P., Piekarski, W., Thomas, B.: Measuring ARTootKit accuracy in long distance tracking experiments. In: Augmented Reality Toolkit, The First IEEE International Workshop (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Hannah Slay
    • 1
  • Bruce Thomas
    • 1
  • Rudi Vernik
    • 1
    • 2
  • Wayne Piekarski
    • 1
  1. 1.e-World Lab, School of Computer and Information ScienceUniversity of South AustraliaMawson LakesAustralia
  2. 2.Defence Science Technology OrganisationEdinburghAustralia

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