EURASIP Journal on Image and Video Processing
Volume 2007 (2007), Article ID 96357, 13 pages
doi:10.1155/2007/96357
Research Article

Color Targets: Fiducials to Help Visually Impaired People Find Their Way by Camera Phone

James Coughlan1 and Roberto Manduchi2

1Rehabilitation Engineering Research Center, Smith-Kettlewell Eye Research Institute, San Francisco 94115, CA, USA
2University of California, Santa Cruz 95064, CA, USA

Received 16 January 2007; Revised 10 May 2007; Accepted 2 August 2007

Academic Editor: Thierry Pun

Copyright © 2007 James Coughlan and Roberto Manduchi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. Coughlan, R. Manduchi, and H. Shen, “Cell phone-based wayfinding for the visually impaired,” in The 1st International Workshop on Mobile Vision, Graz, Austria, May 2006.
  2. W. Crandall, B. Bentzen, L. Myers, and J. Brabyn, “New orientation and accessibility option for persons with visual impairment: transportation applications for remote infrared audible signage,” Clinical and Experimental Optometry, vol. 84, no. 3, pp. 120–131, 2001.
  3. A. M. Ladd, K. E. Bekris, A. P. Rudys, D. S. Wallach, and L. E. Kavraki, “On the feasibility of using wireless ethernet for indoor localization,” IEEE Transactions on Robotics and Automation, vol. 20, no. 3, pp. 555–559, 2004.
  4. M. S. Uddin and T. Shioyama, “Bipolarity- and projective invariant-based zebra-crossing detection for the visually impaired,” in Proceedings of the 1st IEEE Workshop on Computer Vision Applications for the Visually Impaired (CVAVI '05), p. 22, San Diego, Calif, USA, June 2005.
  5. P. Silapachote, J. Weinman, A. Hanson, R. Weiss, and M. A. Mattar, “Automatic sign detection and recognition in natural scenes,” in Proceedings of the 1st IEEE Workshop on Computer Vision Applications for the Visually Impaired (CVAVI '05), p. 27, San Diego, Calif, USA, June 2005.
  6. Y. Cho and U. Neumann, “Multi-ring color fiducial systems for scalable fiducial tracking augmented reality,” in Proceedings of the IEEE Virtual Reality Annual International Symposium (VRAIS '98), p. 212, Atlanta, Ga, USA, March 1998.
  7. D. Claus and A. W. Fitzgibbon, “Reliable fiducial detection in natural scenes,” in Proceedings of the 8th European Conference on Computer Vision (ECCV '04), vol. 4, pp. 469–480, Prague, Czech Republic, May 2004.
  8. L. Naimark and E. Foxlin, “Circular data matrix fiducial system and robust image processing for a wearable vision-inertial self-tracker,” in Proceedings of the International Symposium on Mixed and Augmented Reality (ISMAR '02), pp. 27–36, Darmstadt, Germany, September-October 2002.
  9. D. Scharstein and A. J. Briggs, “Real-time recognition of self-similar landmarks,” Image and Vision Computing, vol. 19, no. 11, pp. 763–772, 2001.
  10. A. State, G. Hirota, D. Chen, W. Garrett, and M. Livingston, “Superior augmented reality registration by integrating landmark tracking and magnetic tracking,” in Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH '96), pp. 429–438, New Orleans, La, USA, August 1996.
  11. A. Zandifar, P. R. Duraiswami, A. Chahine, and L. S. Davis, “A video based interface to textual information for the visually impaired,” in Proceedings of the 4th IEEE International Conference on Multimodal Interfaces (ICMI '02), pp. 325–330, Pittsburgh, Pa, USA, October 2002.
  12. J. Liang, D. Doermann, and H. Li, “Camera-based analysis of text and documents: a survey,” International Journal on Document Analysis and Recognition, vol. 7, no. 2-3, pp. 84–104, 2005.
  13. X. Chen and A. L. Yuille, “Detecting and reading text in natural scenes,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '04), vol. 2, pp. 366–373, Washington, DC, USA, June-July 2004.
  14. J. Gao and J. Yang, “An adaptive algorithm for text detection from natural scenes,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '01), vol. 2, pp. 84–89, Kauai, Hawaii, USA, December 2001.
  15. A. K. Jain and B. Yu, “Automatic text location in images and video frames,” Pattern Recognition, vol. 31, no. 12, pp. 2055–2076, 1998.
  16. H. Li, D. Doermann, and O. Kia, “Automatic text detection and tracking in digital video,” IEEE Transactions on Image Processing, vol. 9, no. 1, pp. 147–156, 2000.
  17. P. Viola and M. Jones, “Rapid object detection using a boosted cascade of simple features,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '01), vol. 1, pp. 511–518, Kauai, Hawaii, USA, December 2001.
  18. B. V. Funt and G. D. Finlayson, “Color constant color indexing,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 17, no. 5, pp. 522–529, 1995.
  19. R. Manduchi and C. Tomasi, “Distinctiveness maps for image matching,” in Proceedings of the 10th International Conference on Image Analysis and Processing, pp. 26–31, Venice, Italy, September 1999.
  20. A. Baumberg, “Reliable feature matching across widely separated views,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '00), vol. 1, pp. 774–781, Hilton Head Island, SC, USA, June 2000.
  21. D. G. Lowe, “Distinctive image features from scale-invariant keypoints,” International Journal of Computer Vision, vol. 60, no. 2, pp. 91–110, 2004.
  22. C. Schmid, R. Mohr, and C. Bauckhage, “Evaluation of interest point detectors,” International Journal of Computer Vision, vol. 37, no. 2, pp. 151–172, 2000.
  23. J. Shi and C. Tomasi, “Good features to track,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '94), pp. 593–600, Seattle, Wash, USA, June 1994.
  24. G. Sharma and H. J. Trussell, “Digital color imaging,” IEEE Transactions on Image Processing, vol. 6, no. 7, pp. 901–932, 1997.
  25. J. Coughlan and R. Manduchi, “Functional assessment of a camera phone-based wayfinding system operated by blind users,” in Conference of IEEE Computer Society and the Biological and Artificial Intelligence Society (IEEE-BAIS), Research on Assistive Technologies Symposium (RAT '07), Dayton, Ohio, USA, April 2007.