Gait Recognition Based on Silhouette, Contour and Classifier Ensembles

  • M. Romero-Moreno
  • J. Fco. Martínez-Trinidad
  • J. A. Carrasco-Ochoa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5197)


Gait Recognition is a non-invasive biometric technique for identifying persons through the way they walk. Currently there are many Gait Recognition methods, most of them based on a similarity function. In this paper, we propose two new methods for Gait Recognition based on silhouette and contour, using a classifier ensemble. Experimental results on a public standard database are shown and compared against others Gait Recognition methods.


Computer vision Gait recognition Classifier ensembles 


  1. 1.
    Jain, A.K.: Biometric Recognition: Overview and Recent Advances. In: Rueda, L., Mery, D., Kittler, J. (eds.) CIARP 2007. LNCS, vol. 4756, pp. 13–19. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  2. 2.
    Nixon, M.S., Carter, J.N.: Automatic Recognition by Gait. Proceedings of the IEEE 94(11), 2013–2024 (2006)CrossRefGoogle Scholar
  3. 3.
    Nixon, M.S., Carter, J.N., Nash, J.M., Huang, P.S., Cunado, D., Stevenage, S.V.: Automatic gait recognition. In: IEE Colloquium Motion Analysis and Tracking, pp. 3/1–3/6 (1999)Google Scholar
  4. 4.
    Murray, M.: Gait as a total pattern of movement. American J. of Physical Medicine 46(1), 290–332 (1967)Google Scholar
  5. 5.
    Dawson, M.R.: Gait recognition, Final Report. Department of Computing Imperial College of Science, Technology & Medicine, London (2002)Google Scholar
  6. 6.
    Lam, T.H.W., Lee, R.S.T., Zhang, D.: Human gait recognition by the fusion of motion and static spatio-temporal templates. Pattern Recognition 40(9), 2563–2573 (2007)CrossRefzbMATHGoogle Scholar
  7. 7.
    Wang, L., Tan, T., Ning, H., Hu, W.: Silhoutte analysis based gait recognition for human identification. IEEE trans Pattern Analysis and Machine Intelligence 25(12), 1505–1518 (2003)CrossRefGoogle Scholar
  8. 8.
    Liu, Z., Sarkar, S.: Simplest representation yet for gait recognition: averaged silhouette. In: IEEE International Conference on Pattern Recognition, pp. 211–214. IEEE Press, Cambridge (2004)Google Scholar
  9. 9.
    Chai, Y., Wang, Q., Jia, J., Zhao, R.: A Novel Human Gait Recognition Method by Segmenting and Extracting the Region Variance Feature. In: 18th International Conference on Pattern Recognition, Hong Kong, vol. 4 (2006)Google Scholar
  10. 10.
    Boulgouris, N.V., Chi, Z.X.: Human gait recognition based on matching of body components. Pattern Recognition 40(6), 1763–1770 (2007)CrossRefzbMATHGoogle Scholar
  11. 11.
    Fazenda, J., Santos, D., Correia, P.: Using Gait to Recognize People. In: Computer as a Tool, EUROCON 2005, vol. 1, pp. 155–158 (2005)Google Scholar
  12. 12.
    Han, J., Bhanu, B.: Human Activity Recognition in Thermal Infrared Imagery. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego (2005)Google Scholar
  13. 13.
    Tan, D., Huang, K., Yu, S., Tan, T.: Efficient Night Gait Recognition Based on Template Matching. In: 18’th International Conference on Pattern Recognition (ICPR 2006), Hong Kong (2006)Google Scholar
  14. 14.
    CASIA Gait Database,

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • M. Romero-Moreno
    • 1
  • J. Fco. Martínez-Trinidad
    • 1
  • J. A. Carrasco-Ochoa
    • 1
  1. 1.Computer Science DepartmentINAOETonantzintlaMéxico

Personalised recommendations