Skip to main content

Sign Language Recognition Using Kinect

  • Conference paper
Artificial Intelligence and Soft Computing (ICAISC 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7267))

Included in the following conference series:

Abstract

An open source framework for general gesture recognition is presented and tested with isolated signs of sign language. Other than common systems for sign language recognition, this framework makes use of Kinect, a depth camera which makes real-time 3D-reconstruction easily applicable. Recognition is done using hidden Markov models with a continuous observation density. The framework also offers an easy way of initializing and training new gestures or signs by performing them several times in front of the camera. First results with a recognition rate of 97% show that depth cameras are well-suited for sign language recognition.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Kelly, D., McDonald, J., Markham, C.: Recognizing Spatiotemporal Gestures and Movement Epenthesis in Sign Language. In: 13th International Machine Vision and Image Processing Conference (IMVIP 2009). IEEE Computer Society, Washington, DC (2009)

    Google Scholar 

  2. Dreuw, P., Rybach, D., Deselaers, T., Zahedi, M., Ney, H.: Speech Recognition Techniques for a Sign Language Recognition System. In: INTERSPEECH 2007, 8th Annual Conference of the International Speech Communication Association (ISCA 2007), pp. 2513–2516 (2007)

    Google Scholar 

  3. Li, X., Parizeau, M., Plamondon, R.: Training Hidden Markov Models with Multiple Observations – A combinatorial Method. IEEE Transactions on PAMI PAMI-22(4), 371–377 (2000)

    Google Scholar 

  4. Vogler, C., Metaxas, D.: ASL Recognition Based on a Coupling Between HMMs and 3D Motion Analysis. In: Proceedings of the Sixth International Conference on Computer Vision, pp. 363–369. Narosa Publishing House (1998) ISBN: 978-8-17319-221-0

    Google Scholar 

  5. Starner, T., Pentland, A.: Real-Time American Sign Language Recognition from Video Using Hidden Markov Models. In: Proceedings of the International Symposium on Computer Vision, ISCV 1995, pp. 265–270. IEEE Publications, U.S (1995) ISBN: 978-0-81867-190-6

    Chapter  Google Scholar 

  6. Boyes Braem, P.: Einführung in die Gebärdensprache und ihre Erforschung. In: Internationale Arbeiten zur Gebärdensprache und Kommunikation Gehörloser, 1st edn., vol. 11. SIGNUM-Verlag (1990) ISBN: 978-3-92773-110-3

    Google Scholar 

  7. Rabiner, L.R.: A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. Proceedings of the IEEE 77(2), 257–286 (1989)

    Article  Google Scholar 

  8. Rahimi, A.: An Erratum for “A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition”, website of Ali Rahimi at MIT Media Laboratory, http://xenia.media.mit.edu/~rahimi/rabiner/rabiner-errata/rabiner-errata.html

  9. Official Microsoft Xbox website, introduction of Kinect, http://www.xbox.com/en-US/kinect

  10. Countdown to Kinect: 17 Controller-Free Games Launch in November, Microsoft News Center, https://www.microsoft.com/presspass/press/2010/oct10/10-18mskinectuspr.mspx

  11. Kinect Downgraded To Save Money, Can’t Read Sign Language, News at Kotaku, http://kotaku.com/5609840/kinect-dumbed-down-to-save-money-cant-read-sign-language

  12. CopyCat and Kinect, overview of the CopyCat Kinect demo on the website of the Center for Accessible Technology in Sign (CATS), http://cats.gatech.edu/content/copycat-and-kinect

  13. Integrating Speech and Hearing Challenge Individuals, YouTube channel of Dr. Natheer Khasawneh, http://www.youtube.com/user/knatheer#p/a/u/1/vVL398dUU5Q

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lang, S., Block, M., Rojas, R. (2012). Sign Language Recognition Using Kinect. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29347-4_46

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-29347-4_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29346-7

  • Online ISBN: 978-3-642-29347-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics