Video-Based Sign Language Content Annotation by Incorporation of MPEG-7 Standard

  • Rashad Aouf
  • Steve Hansen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3579)


The advanced progress in multimedia technology increases the demand on delivering effective content in term of quality with the ability to describe content. From the W3C initiative into the web accessibility (WAI), there is a dedicated effort to make data accessible by every person even by people with disabilities. Accordingly, this paper balances the portion between the minimum bandwidth and the optimum required data to display customized video-based sign language. It also describes a systematic approach derived from the MPEG-7 multimedia content description standard to annotate sign language information. A new approach is proposed by this paper. It makes use of an “intermediary” signage object rather than immediate transmission of sign language video clips. Based on the signage object, this research analyses the components in order to enhance the display quality for video-based sign language with less data consumption by determining the accurate display parameters.


Sign Language Minimum Bandwidth Display Quality Intermediary Object Multimedia Description Scheme 
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.


  1. 1.
    Agrafiotis, D., Canagarajah, N.: Perceptually Optimized Aign Language Video Coding based on Eye Tracking Analysis. Electronics letters 39 (2003)Google Scholar
  2. 2.
    Aouf, R., Hansen, S.: Integration of Signage Information into the Web Environment. In: Miesenberger, K., Klaus, J., Zagler, W.L., Burger, D. (eds.) ICCHP 2004. LNCS, vol. 3118, pp. 1071–1078. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  3. 3.
    Aouf, R., Hansen, S., Salter, G.: Incorporation of Signage Information with Multimedia Data Processing by Making Use of XML Technology. In: Proceedings of the International Conference on Computers in Education, ICCE 2004, Melbourn, Australia,Google Scholar
  4. 4.
    Brewer, J.: Scenarios of People with Disabilities Using the Web (2000)Google Scholar
  5. 5.
    Brewer, J.: WebAccessibility Initiative WAI (2003)Google Scholar
  6. 6.
    Elliott, R., Glauert, J., Kennaway, J., Marshall, I.: The Development of Language Processing Support for the ViSiCAST Project. In: Proceedings of the Fourth International ACM Conference on Assistive Technologies, Virginia, USA (2000)Google Scholar
  7. 7.
    Foulds, R., A.: Biomechanical and Perceptual Constraints on the Bandwidth Requirements of Sign Language. IEEE 12, 65–72 (2004)Google Scholar
  8. 8.
    Han, W., Buttler, D., Pu, C.: Wrapping Web data into XML. SIGMOD 30 (2001)Google Scholar
  9. 9.
    Hunter, J.: An Overview of the MPEG-7 Descripiton Definition Language (DDL). IEEE Transactions on Circuits and Systems for Video Technology, 765–772 (2001)Google Scholar
  10. 10.
    Manoranjan, M., D.: Practical Low-Cost Visual Communication Using Binary Images for Deaf Sign Language. IEEE 8, 81–88 (2000)Google Scholar
  11. 11.
    Martinez, J.,M.: Overview of the MPEG-7 Standard V5.0, ISO/IEC JTC1/SC29/WG11 N4031 Coding of Moving Pictures and Audio: Singapore, pp. 1–88 (2001)Google Scholar
  12. 12.
    Pereira, F.: MPEG-7 Application Document, ISO/IEC JTC1/SC29/WG11 MPEG98/N2462 Coding of Moving Pictures and Audio: Atlantic City, pp. 1–25 (1998)Google Scholar
  13. 13.
    Pereira, F.: MPEG-7 Requirements Document V.15, ISO/IEC JTC1/SC29/WG11 N4317 Coding of Moving Pictures and Audio: Sydney, pp. 1–30 (2001)Google Scholar
  14. 14.
    Salembier, P., Smith, J.,R.: MPEG-7 Multimedia Description Schemes. IEEE Transactions on Circuits and Systems for Video Technology, 748–759 (2001)Google Scholar
  15. 15.
    Sandini, G., Nielsen, J.: Image-based Personal Communication Using an Innvative Space-Variant CMOS Sensor (1997)Google Scholar
  16. 16.
    University, D.: The DePaul University American Sign Language Project. School of Computer Science, Telecommunication and Information Systems, Chicago (2002)Google Scholar
  17. 17.
    University, D.: The DePaul University American Sign Language Project Overview, School of Computer Science, Telecommunication and Information Systems, Chicago (2002)Google Scholar
  18. 18.
    University, D.C.: Research Studentships in the School of Computer, School of Computing (2003)Google Scholar
  19. 19.
    University, G.: Gallaudet University: E-Learning Online Graduate Degrees (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Rashad Aouf
    • 1
  • Steve Hansen
    • 1
  1. 1.School of Computing and Information TechnologyUniversity of Western SydneySydneyAustralia

Personalised recommendations