Skip to main content

Advertisement

Springer Nature Link
Log in

Optimized H.264 compression of sign language video

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

In TV broadcasting deaf people are not able to get information from the audio content. In public television, some programs may be accompanied by a sign language interpreter as a part of the broadcasted signal. As a supplementary service, it would enable more programs to be accessible with a sign language interpreter to assist in comprehension. To be able to transmit such data flow separately, we define the parameters of compression of sign language interpreter image to ensure intelligibility and quality while maintaining low bitrate. This paper deals with specific video compression of Czech sign language interpreter based on regions of interest implemented to the ×264 open source library. The results of this approach are verified in subjective tests with the deaf and hearing evaluators. The experiments examine the intelligibility of sign language expressions containing minimal pairs for different levels of image compression and also evaluate the subjective quality of the final image.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

Notes

  1. Video compression standard by the ITU-T Video Coding Experts Group (VCEG) originally designed as a low-bit-rate format for videoconferencing.

  2. Haar features indicate regularities (some similar properties) shared by all human faces.

References

  1. Agrafiotis D et al. (2006) A perceptually optimised video coding system for sign language communication at lowbit rates. Signal Process Image Commun 21(7):531–549

    Article  Google Scholar 

  2. Cavender A, et al (2006) Mobile ASL:: intelligibility of sign language video as constrained by mobile phone technology, in Proceedings of the 8th international ACM SIGACCESS conference on Computers and accessibility (Portland, October 22–25), 71–78

  3. Ciaramello FM, Hemami SS (2011) A computational intelligibility model for assessment and compression of American sign language video. IEEE Trans Image Process 20(11):3014–3027

    Article  MathSciNet  Google Scholar 

  4. Emmorey K, Thompson R, Colvin R (2009) Eye gaze during comprehension of American sign language by native and beginning signers. J Deaf Stud Deaf Educ 14(2):237–243

    Article  Google Scholar 

  5. Freund Y, Shapire R (1995) A decision-theoretic generalization of on-line learning and an application to boosting, In Proceedings of the Second European Conference on Computational Learning Theory, 23–33

  6. HbbTV official websites http://www.hbbtv.org/. Accessed 10 Dec 2015

  7. ITU-R Recommendation BT.500–13 (2012c) Methodology for the subjective assessment of the quality of television pictures. Technical report

  8. Laidler CH (2010) Open mobile video communication for the deaf. Dissertation, University of Cape Town

  9. Mittal A, Zisserman A, Torr PH (2011) Hand detection using multiple proposals. In British Machine Vision Conference, pp 1–11

  10. Nakazono K, Nagashima Y, Ichikawa A (2006) Digital encoding applied to sign language video. IEICE Trans Inf Syst E89-D(6):1893–1900

    Article  Google Scholar 

  11. Sign language translation services - HBB4ALL, http://www.hbb4all.eu/home/hbb4allpilots/pilot-d-sign-language-translation-service/.

  12. Svachula Z, Bernas M, Zatloukal P, Klabanova L (2013) Investigation of Regions of Interest for Deaf in Czech Sign Language Content. IJSWS 3, 44–49

  13. The results of the sample survey of disabled people in 2007. (Czech statistical office, 2008), http://www.czso.cz/csu/2008edicniplan.nsf/p/3309-08. Accessed 1 Nov 2015

  14. Viola P, Jones MJ (2004) Robust real-time face detection. Int J Comput Vis 57:137–154

    Article  Google Scholar 

  15. Zatloukal P, Bernas M, Dvorak L (2014) Independent transmission of sign language interpreter in DVB: assessment of image compression, In Seventh International Conference on Machine Vision (ICMV 2014)

Download references

Acknowledgments

This work was supported by the Grant Agency of the Czech Technical University in Prague, grant No. SGS15/089/OHK3/1 T/13.

Author information

Authors and Affiliations

  1. Department of Radio Engineering, Faculty of Electrical Engineering, Czech Technical University (CTU) in Prague, Technicka 2, 166 27, Prague, Czech Republic

    Petr Zatloukal & Martin Bernas

Authors
  1. Petr Zatloukal
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Martin Bernas
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Petr Zatloukal.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zatloukal, P., Bernas, M. Optimized H.264 compression of sign language video. Multimed Tools Appl 76, 16225–16237 (2017). https://doi.org/10.1007/s11042-016-3905-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-016-3905-1

Keywords