Skip to main content
SpringerLink
Log in

Implementation of Gait Recognition for Surveillance Applications

  • Conference paper
  • First Online:
Microelectronics, Electromagnetics and Telecommunications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 372))

Abstract

There are various biometric measures that are used in industrial applications for identification of a human. They are signature verification, face recognition method, voice, iris recognition methods, and recognition using digital signatures. These existing human recognition methods have the following limitations of not being unique, low reliability, and could easily traceable by intruders. Gait is the walking style of a human. Gait can be recognized from a view-based approach. In this approach two different image features are required; they are the width of the outer contour of the silhouette and entire binary silhouette. Observation vector can be obtained from the image feature by modeling the frame to exemplar distance (FED) vector sequence with Hidden Markov Model (HMM) as it provides robustness to recognition. In this paper an effort is made for gait recognition useful in real time surveillance applications.

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 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
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. A. Kale, A. Sundaresan, A.N. Rajagopalan, N.P. Cuntoor, A.K. Roy-Chowdhury, V. Kruger, R. Chellappa, Identification of humans using gait. Image Process. IEEE Trans. 13(9), 1163–1173 (2004)

    Article  Google Scholar 

  2. A. Elgammal, D. Harwood, L. Davis, Non-parametric model for background subtraction. in Proceedings of the IEEE FRAME-RATE Workshop, 1999

    Google Scholar 

  3. L. Lee, W.E.L. Grimson, Gait analysis for recognition and classification. in Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition, May 2002

    Google Scholar 

  4. A. Kale, A. Sundaresan, A.K. Roychowdhury, R. Chellappa, Gait-based human identification from a monocular video sequence. in Handbook on Pattern Recognition and Computer Vision, 3rd edn. (World Scientific Publishing Company Pvt. Ltd., 2004)

    Google Scholar 

  5. R. Zhang, Ch. Vogler, D. MetaXas, Human gait recognition at sagittal plane. Image Vision Comput. 25(3), 321–330,(2007)

    Google Scholar 

  6. B. Fadaei, A. Behrad, Human Identification Using Motion Information and Digital Video Processing, in 7th Iranian Machine Vision and Image Processing (MVIP) 2011, pp. 1–6, 16–17 Nov 2011. doi:10.1109/IranianMVIP.2011.6121603

  7. L.R. Rabiner, A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE 77, 257–285 (1989)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of ECE, JNTUK UCEV, Vizianagaram, A.P., India

    K. Babulu, N. Balaji, M. Hema & A. Krishnachaitanya

Authors
  1. K. Babulu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. N. Balaji
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. Hema
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. A. Krishnachaitanya
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to K. Babulu .

Editor information

Editors and Affiliations

  1. Dept of Computer Science Engineering, Anil Neerukonda Institute of Techn. and Sciences, Vishakapatnam, India

    Suresh Chandra Satapathy

  2. Electronics & Communication Engineering, National Institute of Technology Electronics & Communication Engineering, Warangal, India

    N Bheema Rao

  3. Electronics & Communication Engineering, Jawaharlal Nehru Technological Univ, Kakinada, Andhra Pradesh, India

    S Srinivas Kumar

  4. Electronics & Communication Engineering, GITAM University Electronics & Communication Engineering, Visakhapatnam, Andhra Pradesh, India

    C Dharma Raj

  5. Electronics & Communication Engineering, GITAM University Electronics & Communication Engineering, Visakhapatnam, Andhra Pradesh, India

    V Malleswara Rao

  6. Electronics & Communication Engineering, GITAM University Electronics & Communication Engineering, Visakhapatnam, India

    G V K Sarma

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer India

About this paper

Cite this paper

Babulu, K., Balaji, N., Hema, M., Krishnachaitanya, A. (2016). Implementation of Gait Recognition for Surveillance Applications. In: Satapathy, S., Rao, N., Kumar, S., Raj, C., Rao, V., Sarma, G. (eds) Microelectronics, Electromagnetics and Telecommunications. Lecture Notes in Electrical Engineering, vol 372. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2728-1_9

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-2728-1_9

  • Published:

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2726-7

  • Online ISBN: 978-81-322-2728-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation