Skip to main content
SpringerLink
Log in

Gait Recognition, Evaluation

  • Reference work entry
  • First Online:
Encyclopedia of Biometrics

  • 205 Accesses

Synonyms

Gait recognition; Progress in gait recognition

Definition

Gait recognition refers to automated methods that use video or other sensory data of human gait to recognize or to identify a person. Evaluation of gait recognition refers to the benchmarking of progress in the design of gait recognition algorithms on standard, common, datasets.

Introduction

Gait recognition refers to the use of human gait to recognize or to identify a person based on their walking styles. It is a manifestation of overall body geometry, i.e., proportions of the limbs, torso, etc., and body physiology, i.e., bones and musculature. Given this diverse range of body attributes involved in its production, there is a strong possibility for large source of variation in gait among individuals and hence in its potential uniqueness. Given the myriad of factors that determine a person’s gait, theoretical modeling of gait is very complex. Thus, the design of gait algorithms is necessarily an iterative process,...

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 899.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 549.99
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. D.K. Wagg, M.S. Nixon, On automated model-based extraction and analysis of gait, in International Conference on Automatic Face and Gesture Recognition, Seoul, 2004, pp. 11–16

    Google Scholar 

  2. S. Sarkar, P. Jonathon Phillips, Z. Liu, I. Robledo-Vega, P. Grother, K.W. Bowyer, The human ID gait challenge problem: data sets, performance, and analysis. IEEE Trans. Pattern Anal. Mach. Intell. 27(2), 162–177 (2005)

    Google Scholar 

  3. S. Yu, D. Tan, T. Tan, A framework for evaluating the effect of view angle, clothing and carrying condition on gait recognition, in International Conference on Pattern Recognition, Hong Kong, vol. 4, 2006, pp. 441–444

    Google Scholar 

  4. D. Tan, K. Huang, S. Yu, T. Tan, Efficient night gait recognition based on template matching, in 18th International Conference on Pattern Recognition, ICPR 2006, Hong Kong, vol. 3, 2006, pp. 1000–1003

    Google Scholar 

  5. M. Okumura, H. Iwama, Y. Makihara, Y. Yagi, Performance evaluation of vision-based gait recognition using a very large-scale gait database, in 2010 Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS), Washington, DC, 2010, pp. 1–6

    Google Scholar 

  6. H. Iwama, M. Okumura, Y. Makihara, Y. Yagi, The ou-isir gait database comprising the large population dataset and performance evaluation of gait recognition. IEEE Trans. Inf. Forensics Secur. 7(5), 1511–1521 (2012)

    Google Scholar 

  7. M. Hofmann, J. Geiger, S. Bachmann, B. Schuller, G. Rigoll, The {TUM} gait from audio, image and depth (gaid) database: multimodal recognition of subjects and traits. J. Vis. Commun. Image Represent. 25(1), 95–206 (2014)

    Google Scholar 

  8. Z. Liu, L. Malave, A. Osuntogun, P. Sudhakar, S. Sarkar, Toward understanding the limits of gait recognition, in Proceedings of SPIE Defense and Security Symposium: Biometric Technology for Human Identification, Orlando, 2004, pp. 195–205

    Google Scholar 

  9. Z. Liu, S. Sarkar, Improved gait recognition by gait dynamics normalization. IEEE Trans. Pattern Anal. Mach. Intell. 28(6), 863–876 (2006)

    Google Scholar 

  10. A. Kale, A. Sundaresan, A.N. Rajagopalan, N.P. Cuntoor, A.K. Roy-Chowdhury, V. Krüger, R. Chellappa, Identification of humans using gait. IEEE Trans. Image Process. 13(9), 1163–1173 (2004)

    Google Scholar 

  11. X. Yang, T. Zhang, Y. Zhou, J. Yang, Gabor phase embedding of gait energy image for identity recognition, in 8th IEEE International Conference on Computer and Information Technology, CIT 2008, Sydney, 2008, pp. 361–366

    Google Scholar 

  12. D. Matovski, M. Nixon, S. Mahmoodi, J. Carter, The effect of time on the performance of gait biometrics, in 2010 Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS), Washington, DC, 2010, pp. 1–6

    Google Scholar 

  13. J.D. Shutler, M.G. Grant, M.S. Nixon, J.N. Carter, On a large sequence-based human gait database, in International Conference on Recent Advances in Soft Computing, Nottingham, 2002, pp. 66–71

    Google Scholar 

  14. C.C. Yang, Y.L. Hsu, A review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors 10(8), 7772–7788 (2010)

    Google Scholar 

  15. D. Gafurov, E. Snekkenes, P. Bours, Gait authentication and identification using wearable accelerometer sensor, in 2007 IEEE Workshop on Automatic Identification Advanced Technologies, Alghero, 2007, pp. 220–225

    Google Scholar 

  16. D. Gafurov, J. Hagen, E. Snekkenes, Temporal characteristics of gait biometrics, in 2010 Second International Conference on Computer Engineering and Applications (ICCEA), Bali Island, vol. 2, 2010, pp. 557–561

    Google Scholar 

  17. C. Nickel, C. Busch, Classifying accelerometer data via hidden Markov models to authenticate people by the way they walk, in 2011 IEEE International Carnahan Conference on Security Technology (ICCST), Barcelona, 2011, pp. 1–6

    Google Scholar 

  18. C. Nickel, T. Wirtl, C. Busch, Authentication of smartphone users based on the way they walk using k-nn algorithm, in 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), Piraeus-Athens, 2012, pp. 16–20

    Google Scholar 

  19. N.T. Trung, Y. Makihara, H. Nagahara, Y. Mukaigawa, Y. Yagi, Performance evaluation of gait recognition using the largest inertial sensor-based gait database, in 2012-5th IAPR International Conference on Biometrics (ICB), New Delhi, 2012, pp. 360–366

    Google Scholar 

  20. G. Doddington, M. Przybocki, A. Martin, D. Reynolds, The NIST speaker recognition evaluation–overview, methodology, systems, results, perspective. Speech Commun. 31(2–3), 225–254 (2000)

    Google Scholar 

  21. G. Veres, M. Nixon, J. Carter, Is enough enough? What is sufficiency in biometric data? Lect. Notes Comput. Sci. 4142, 262 (2006)

    Google Scholar 

  22. R. Panchumarthy, R. Subramanian, S. Sarkar, Biometric evaluation on the cloud: a case study with HumanID gait challenge, in 2012 IEEE Fifth International Conference on Utility and Cloud Computing (UCC), Chicago, 2012, pp. 219–222

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science and Engineering, University of South Florida, Tampa, FL, USA

    Sudeep Sarkar & Ravichandran Subramanian

  2. Personal device, Device and Services, Microsoft Corporation, Redmond, WA, USA

    Zongyi Liu

Authors
  1. Sudeep Sarkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ravichandran Subramanian
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zongyi Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Center for Biometrics and Security, Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Stan Z. Li

  2. Departments of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA

    Anil K. Jain

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Science+Business Media New York

About this entry

Cite this entry

Sarkar, S., Subramanian, R., Liu, Z. (2015). Gait Recognition, Evaluation. In: Li, S.Z., Jain, A.K. (eds) Encyclopedia of Biometrics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7488-4_39

Download citation

Publish with us

Policies and ethics

Search

Navigation