Skip to main content

Research on Algorithm and Model of Hand Gestures Recognition Based on HMM

  • Conference paper
  • First Online:
Book cover Cloud Computing, Security, Privacy in New Computing Environments (CloudComp 2016, SPNCE 2016)

Abstract

Human computer interaction is one of the key points in the competition of information industry in the world, all countries in the world put the human-computer interaction as a key technology to study. Butler Lampson, ACM Turing Award winner in 1992 and Microsoft Research Institute chief software engineer pointed out that the computer has three functions in the “21st century computing research” report. The first is simulation; the second is that the computer can help people to communicate; the third is interaction, that is, to communicate with the real world. Human-computer interaction is an important field of computer research, and hand gestures recognition is a key technology in this field. The key of gesture recognition is the feature extraction and the establishment of hand recognition model. It can accurately identify the various kinds of deformation. HMM method has a flexible and efficient training and recognition algorithm, if the system needs to add a new gesture, just need to train the gesture of the sample set can be; If a gesture is not needed, just delete the corresponding HMM algorithm of the gesture, HMM has a strong expansion. Compared with DTW and other methods, HMM in speech recognition, gesture recognition, the recognition effect is better. In this paper, the HMM algorithm is used to identify the typical gestures, got very good recognition effect.

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 EPUB and 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

References

  1. Ma, C., Ren, L., Teng, D., Wang, H., Dai, G.: Ubiquitous human-computer interaction in cloud manufacturing. Comput. Integr. Manuf. Syst. 17(03), 504–510 (2011)

    Google Scholar 

  2. Fang, Z., Wu, X., Ma, W.: The progress on the study of human computer interaction technology. Comput. Eng. Des. 19(01), 57–63 (1998)

    Google Scholar 

  3. Gao, N.: Research on gesture recognition technology based on vision. Hebei University of Technology (2015)

    Google Scholar 

  4. ITU: ITU Internet reports 2005: the Internet of things. ITU, Geneva, Switzerland (2005)

    Google Scholar 

  5. Guan R., Xu, X., Luo, Y., Miao, J., Qiu, S.: A computer vision-based gesture detection and recognition technique. Comput. Appl. Softw. (01) (2013)

    Google Scholar 

  6. Marcus, A., van Dam, A.: User-interface developments for the nineties. IEEE Comput. 24(9), 49–57 (1991)

    Article  Google Scholar 

  7. Wang, J.: Integration of eye-gaze, voice and manual response in multimodel user interface. In: Proceedings of IEEE International Conference on Systems, Man and Cybernetics, vol. 15 (1995)

    Google Scholar 

  8. Wang, L.: Dynamic gesture tracking and recognition and human computer interaction technology research. Xidian University (2014)

    Google Scholar 

  9. Wang, Q., Qi, X., Jiang, Y., Xu, W.: 3D handwriting recognition method based on hidden Markov models. Appl. Res. Comput. 09, 099 (2012)

    Google Scholar 

  10. Fan, Z.: Parallel gesture recognition system based on depth learning in complex background. Xidian University (2014)

    Google Scholar 

  11. Qu, Q.Y.: The gesture recognition depth image and dexterous hand based interaction. Shanghai University (2014)

    Google Scholar 

  12. Wang, D.: Based on gesture recognition method of human-computer interaction system. Lanzhou University of Technology (2013)

    Google Scholar 

  13. Hu, W.: The research of human-computer interaction system based on gesture. Wuhan University of Technology (2010)

    Google Scholar 

  14. Tan, D.: Research on vision-based dynamic hand gesture recognition. Harbin Institute of Technology (2014)

    Google Scholar 

Download references

Acknowledgment

This work is funded by Yunnan Enterprises Key Laboratory of Traffic Engineering Test Center (JTGC-2015-003).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Junhui Liu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Liu, J., Liao, Y., He, Z., Yang, Y. (2018). Research on Algorithm and Model of Hand Gestures Recognition Based on HMM. In: Wan, J., et al. Cloud Computing, Security, Privacy in New Computing Environments. CloudComp SPNCE 2016 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 197. Springer, Cham. https://doi.org/10.1007/978-3-319-69605-8_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-69605-8_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69604-1

  • Online ISBN: 978-3-319-69605-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics