Skip to main content
SpringerLink
Log in

A Neural-Network-Based Hand Posture Recognition Method

  • Conference paper
  • First Online:
Transactions on Engineering Technologies

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 275))

Abstract

In various pattern recognition applications, angle variation is always a main challenging factor for producing reliable recognition. To increase the endurance ability on angle variation, this paper adopts a Hierarchical Temporal Memory (HTM) algorithm which applies temporal information to organize time-sequence change of image features, and constructs invariant features so that the influence of angle variation can be effectively learnt and overcome. The proposed multi-angle HTM-based posture recognition method consists of two main modules of Hand Posture Image Pre-processing (HPIP) and Hand Posture Recognition (HPR). In HPIP, each input image is first processed individually by skin color detection, foreground segmentation and edge detection. Then, the three processed results are further combined linearly to locate a hand posture region. In HPR, the normalized image is forwarded to a HTM model for learning and recognizing of different kinds of hand postures. Experiment results show that when using the same continuous unconstrained hand posture database, the proposed method can achieve an 89.1 % high recognition rate for discriminating three kinds of hand postures, which are scissors, stone and paper, and outperforms both Adaboost (78.1 %) and SVM (79.9 %).

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover 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. Echtler F et al (2010) An LED-based multitouch sensor for LCD screens. In: Proceedings of the ACM tangible and embedded interaction conference, pp 227–230

    Google Scholar 

  2. Xie L, Liu Z (Apr. 2007) Realistic mouth-synching for speech-driven talking face using articulatory modelling. Proc IEEE Trans Multimedia 9(3):500–510

    Google Scholar 

  3. Cucchiara R et al (2003) Detecting moving objects. Ghosts, and shadows in video streams. Proc IEEE Trans Pattern Anal Mach Intell 25(10):1337–1342

    Article  Google Scholar 

  4. McIvor AM (2000) Background subtraction techniques. In: Proceedings of the image and vision computing. Auckland, New Zealand

    Google Scholar 

  5. Murali S, Girisha R (2009) Segmentation of motion objects from surveillance video sequences using temporal differencing combined with multiple correlation. In: Proceedings of the IEEE international conference on advanced video and signal based surveillance, pp 472–477

    Google Scholar 

  6. Sun S et al (2000) Motion estimation based on optical flow with adaptive gradients. In: Proceedings of the IEEE international conference on image processing, vol 1, pp 852–855

    Google Scholar 

  7. Kim K et al (2005) Real-time foreground-foreground segmentation using codebook model. In: Proceedings of the real-time imaging, vol 11(3), pp 172–185

    Google Scholar 

  8. Chai D, Bouzerdoum A (2000) A Bayesian approach to skin color classification inYCbCr color space. In: Proceedings of the IEEE region ten conference, vol 2. Kuala Lumpur, Malaysia, pp 421–424

    Google Scholar 

  9. Hawkins J, George D (2006) Hierarchical temporal memory concepts, theory, and terminology, numenta, http://www.numenta.com/htm-overview/education/Numenta_HTM_Concepts.pdf

  10. Hawkins J, Balkeslee S (2004) On Intelligence. Owl Books, New York

    Google Scholar 

  11. Vutsinas CN et al (2008) A neocortex model implementation on reconfigurable logic with streaming memory. In: Proceedings of the IEEE international symposium parallel and distributed processing, pp 1–8

    Google Scholar 

  12. Johnson SC (1967) Hierarchical clustering schemes. Proc Springer J Pyschometrika 32(3):241–254

    Article  Google Scholar 

  13. Huang Y-S, Wang Y-J (2013) Multi-angle hand posture recognition based on hierarchical temporal memory.docx. In: Proceedings of the international multiconference of engineers and computer scientists 2013, Hong Kong, pp 70–75, 13–15 March 2013

    Google Scholar 

Download references

Acknowledgments

This work was supported by National Science Institute, Republic of China, under grants NSC NSC 101-2221-E-216-037-MY2.

Author information

Authors and Affiliations

  1. Department of Computer Science and Information Engineering, Chung-Hua University, No. 707, Sec. 2, WuFu. Rd., Hsinchu, Taiwan

    Yea Shuan Huang & Yun Jiun Wang

Authors
  1. Yea Shuan Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yun Jiun Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yea Shuan Huang .

Editor information

Editors and Affiliations

  1. Department of Multimedia Engineering College of Engineering, Mokpo National University, Chonnam, Korea, Republic of (South Korea)

    Gi-Chul Yang

  2. International Association of Engineers, Hong Kong, Hong Kong SAR

    Sio-Iong Ao

  3. Faculty of Information Sciences and Engineering, University of Canberra, Canberra, Aust Capital Terr, Australia

    Xu Huang

  4. Computer Sci. in the Graduate Division, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media Dordrecht

About this paper

Cite this paper

Huang, Y.S., Wang, Y.J. (2014). A Neural-Network-Based Hand Posture Recognition Method. In: Yang, GC., Ao, SI., Huang, X., Castillo, O. (eds) Transactions on Engineering Technologies. Lecture Notes in Electrical Engineering, vol 275. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7684-5_14

Download citation

  • DOI: https://doi.org/10.1007/978-94-007-7684-5_14

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-7683-8

  • Online ISBN: 978-94-007-7684-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation