Encyclopedia of Biometrics

2015 Edition
| Editors: Stan Z. Li, Anil K. Jain

Footstep Recognition

  • Rubén Vera Rodriguez
  • Nicholas Evans
  • John S. D. Mason
Reference work entry
DOI: https://doi.org/10.1007/978-1-4899-7488-4_41

Synonyms

Footstep identification; Footstep verification

Definition

Footstep recognition is a relatively new biometric and is based on the study of footstep signals captured from persons walking over an instrumented sensing area. Since the biometric information is embedded in a time-varying signal, thereby implying some form of action (e.g., in this case those of walking or running), footsteps can be included in the group of behavioral biometrics.

Introduction

Footstep recognition was first suggested as a biometric in 1977 by Pedotti [1], but it was not until 1997 when Addlesee et al. [2] reported the first experiments. Since then the subject has received relatively little attention in the literature, and so it is perhaps of little surprise that reported performances fall short of those achievable with other, more popular, and researched biometrics. However, recent work has demonstrated the real potential of the footstep biometric which is certainly not without its appeal.

One...

This is a preview of subscription content, log in to check access

References

  1. 1.
    A. Pedotti, Simple equipment used in clinical practice for evaluation of locomotion. IEEE Trans. Biomed. Eng. BME-24(5), 456–461 (1977)Google Scholar
  2. 2.
    M.D. Addlesee, A. Jones, F. Livesey, F. Samaria, The ORL active floor. IEEE Pers. Commun. 4(5), 35–41 (1997)Google Scholar
  3. 3.
    Y. Shoji, T. Takasuka, H. Yasukawa, Personal identification using footstep detection, in Proceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, Seoul (2004), pp. 43–47Google Scholar
  4. 4.
    H. Morishita, R. Fukui, T. Sato, High resolution pressure sensor distributed floor for future human-robot symbiosis environments, in Proceedings of 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems, Lausanne, vol. 2 (2002), pp. 1246–1251Google Scholar
  5. 5.
    T. Murakita, T. Ikeda, H. Ishiguro, Human tracking using floor sensors based on the Markov chain Monte Carlo method, in Proceedings of the 17th International Conference on Pattern Recognition (ICPR), Cambridge, vol. 4 (2004), pp. 917–920Google Scholar
  6. 6.
    J.S. Yun, S.H. Lee, W.T. Woo, J.H. Ryu, The user identification system using walking pattern over the ubiFloor, in Proceedings of International Conference on Control, Automation, and Systems, Montreal (2003), pp. 1046–1050Google Scholar
  7. 7.
    L. Middleton, A.A. Buss, A.I. Bazin, M.S. Nixon, A floor sensor system for gait recognition, in Proceedings of Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AutoID’05), Buffalo (2005), pp. 171–176Google Scholar
  8. 8.
    P. Srinivasan, D. Birchefield, G. Qian, A. Kidane, A pressure sensing floor for interactive media applications, in Proceedings of the 2005 ACM SIGCHI International Conference, Valencia, vol. 265 (2005), pp. 278–281Google Scholar
  9. 9.
    R.J. Orr, G.D. Abowd, The smart floor: a mechanism for natural user identification and tracking, in Proceedings of Conference on Human Factors in Computing Systems, The Hague (2000), pp. 275–276Google Scholar
  10. 10.
    C. Cattin, Biometric authentication system using human Gait. Swiss Federal Institute of Technology, Zurich. PhD Thesis (2002)Google Scholar
  11. 11.
    J. Suutala, S. Pirttikangas, J. Riekki, J. Roning, Reject-optional LVQ-based two-level classifier to improve reliability in footstep identification, in Lecture Notes in Computer Science, ed. by A. Ferscha, F. Mattern, vol. 3001 (Springer, Berlin, 2004), pp. 182–187, http://www.springer.com/new+%26+forthcoming+titles+%28default%29/book/978-3-540-21835-7
  12. 12.
    Y. Gao, M.J. Brennan, B.R. Mace, J.M. Muggleton, Person recognition by measuring the ground reaction force due to a footstep, in Proceedings of Ninth International Conference on Recent Advances in Structural Dynamics, Southampton (2006)Google Scholar
  13. 13.
    R. Vera-Rodriguez, N.W.D. Evans, R.P. Lewis, B. Fauve, J.S.D. Mason, An experimental study on the feasibility of footsteps as a biometric, in Proceedings of 15th European Signal Processing Conference (EUSIPCO’07), Poznan (2007), pp. 748–752Google Scholar
  14. 14.
    J. Suutala, J. Roning, Towards the adaptive identification of walkers: automated feature selection of footsteps using distinction-sensitive LVQ, in Proceedings of International Workshop on Processing Sensory Information for Proactive Systems, Oulu (2004), pp. 61–67Google Scholar
  15. 15.
    R. Vera-Rodriguez, R.P. Lewis, N.W.D. Evans, J.S.D. Mason, Optimisation of geometric and holistic feature extraction approaches for a footstep biometric verification system, in Proceedings International Summer School for Advanced Studies on Biometrics for Secure Authentication, Alghero (2007)Google Scholar
  16. 16.
    G.P. Mazarakis, J.N. Avaritsiotis, A prototype sensor node for footstep detection, in Proceedings of the Second European Workshop on Wireless Sensor Networks, Istanbul (2005), pp. 415–418Google Scholar
  17. 17.
    T. Mori, T. Sato, K. Asaki, Y. Yoshimoto, Y. Kishimoto, One-room-type sensing system for recognition and accumulation of human behavior, in Proceedings of 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems, Takamatsu, vol. 1 (2000), pp. 344–350Google Scholar
  18. 18.
    R. Headon, R. Curwen, Recognizing movements from the ground reaction force, in Proceedings of the 2001 Workshop on Perceptive User Interfaces, Orlando, vol. 15 (2001), pp. 1–8Google Scholar
  19. 19.
    W.H. Liau, C.L. Wu, L.C. Fu, Inhabitants tracking system in a cluttered home environment via floor load sensors. IEEE Trans. Autom. Sci. Eng. 5(1), 10–20 (2008)Google Scholar
  20. 20.
    J. Paradiso, C. Abler, K. Hsiao, M. Reynolds, The magic carpet: physical sensing for immersive environments, in Proceedings of CHI’97, Atlanta (1997), pp. 277–278Google Scholar
  21. 21.
    J. Paradiso, E. Hu, Expressive footwear for computer-augmented dance performance, in Proceedings of the First International Symposium on Wearable Computers, Cambridge. IEEE Computers Society Press, Cambridge (1997), pp. 165–166Google Scholar
  22. 22.
    J. Suutala, J. Roning, Combining classifiers with different footstep feature sets and multiple samples for person identification, in Proceedings of International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Philadelphia, vol. 5 (2005), pp. 357–360Google Scholar
  23. 23.
    S.U., Footstep recognition at Swansea University. Available at http://eeswan.swan.ac.uk

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Rubén Vera Rodriguez
    • 1
  • Nicholas Evans
    • 2
  • John S. D. Mason
    • 3
  1. 1.Swansea UniversitySwanseaUK
  2. 2.EURECOMBiotFrance
  3. 3.Swansea UniversitySwanseaUK