Cluster Tagging: Robust Fiducial Tracking for Smart Environments
Fiducial scene markers provide inexpensive vision-based location systems that are of increasing interest to the Pervasive Computing community. Already established in the Augmented Reality (AR) field, markers are cheap to print and straightforward to locate in three dimensions. When used as a component of a smart environment, however, there are issues of obscuration, insufficient camera resolution and limited numbers of unique markers.
This paper looks at the advantages of clustering multiple markers together to gain resilience to these real world problems. It treats the visual channel as an erasure channel and relevant coding schemes are applied to decode data that is distributed across the marker cluster using an algorithm that does not require each tag to be individually numbered. The advantages of clustering are determined to be a resilience to obscuration, more robust position and pose determination, better performance when attached to inconvenient shapes, and an ability to encode more than a database key into the environment. A real world example comparing the positioning capabilities of a cluster of tags with that of a single tag is presented. It is apparent that clustering provides a position estimate that is more robust, without requiring external definition of a co-ordinate frame using a database.
KeywordsAugmented Reality Ubiquitous Computing Camera Position Mixed Reality Smart Environment
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- 1.Harle, R.K., Rice, A., Beresford, A.R.: Cantag. In: Proceedings of the Fourth Annual IEEE International Conference on Pervasive Computer and Communications (PerCom), Pisa, Italy, March 13-17 (2006)Google Scholar
- 2.Billinghurst, M., Kato, H., Poupyrev, I.: The MagicBook: Moving seamlessly between reality and virtuality. IEEE Computer Graphics and Applications, 2–4 (May 2001)Google Scholar
- 3.Billinghurst, M., Kato, H., Poupyrev, I.: The MagicBook—moving seamlessly between reality and virtuality. IEEE Computer Graphics and Applications 21(3), 6–8 (2001)Google Scholar
- 4.Billinghurst, M., Kato, H.: Collaborative mixed reality. In: Proceedings of the First International Symposium on Mixed Reality, pp. 261–284 (1999)Google Scholar
- 6.Fiala, M.: ARTag revision 1, a fiducial marker system using digital techniques. Technical report, National Research Council Canada (2004)Google Scholar
- 7.Hightower, J., Borriello, G.: Location sensing techniques. IEEE Computer (August 2001)Google Scholar
- 8.Kato, H., Billinghurst, M., Poupyrev, I., Imamoto, K., Tachibana, K.: Virtual object manipulation on a table-top AR environment. In: Proceedings of ISAR 2000 (October 2000)Google Scholar
- 10.Rekimoto, J.: Matrix: A realtime object identification and registration method for augmented reality. In: Proceedings of Asia Pacific Computer Human Interaction, July 1998, pp. 63–68 (1998)Google Scholar
- 11.Rice, A., Cain, C., Fawcett, J.: Dependable coding for fiducial tags. In: Proceedings of the 2nd Ubiquitous Computing Symposium, pp. 155–163 (2004)Google Scholar
- 12.Rice, A., Harle, R.: Evaluating lateration-based positioning algorithms for fine-grained tracking. In: Proceedings of the Joint Workshop on Foundations of Mobile Computing (DIAL-M-POMC) 2005, ACM Press, New York (2005)Google Scholar
- 14.Neumann, U., You, S., Cho, Y.: Augmented Reality Tracking in Natural Environments. In: Ohta, Y., Tamura, H. (eds.) Mixed Reality - Merging Real and Virtual Worlds, pp. 101–130. Ohmsha and Springer (1999)Google Scholar
- 16.Want, R.: RFID: A key to automating everything. Scientific American, 56–65 (January 2003)Google Scholar