Towards Robust Gait Recognition

  • Tenika P. Whytock
  • Alexander Belyaev
  • Neil M. Robertson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8034)


Covariate factors, such as persons carrying a bag and wearing a jacket, continue to cause significant misclassification in gait recognition. A novel and efficient approach learns a “typical” Gait Energy Image representation free from covariate factors which aids their mitigation in test and training data. Combating the influence of covariate factors yields a significant improvement of 11% over existing state of the art performance for sequences capturing persons wearing a jacket.


Linear Discriminant Analysis Covariate Factor Energy Image Gait Recognition Gait Energy Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Murray, M., Drought, A., Kory, R.: Walking patterns of normal men. The Journal of Bone and Joint Surgery 46, 335–360 (1964)Google Scholar
  2. 2.
    Cutting, J., Kozlowski, L.: Recognising friends by their walk: gait perception without familiarity cues. Bulletin of the Psychonomic Society 9, 353–356 (1977)CrossRefGoogle Scholar
  3. 3.
    Rudoy, D., Zelnik-Manor, L.: Viewpoint selection for human actions. International Journal of Computer Vision 97, 243–254 (2012)CrossRefGoogle Scholar
  4. 4.
    Bashir, K., Xiang, T., Gong, S.: Feature selection for gait recognition without subject cooperation. In: Proceedings of the British Machine Vision Conference (BMVC) (2008)Google Scholar
  5. 5.
    Bashir, K., Xiang, T., Gong, S.: Gait representation using flow fields. In: Proceedings of the British Machine Vision Conference (BMVC) (2009)Google Scholar
  6. 6.
    Bashir, K., Xiang, T., Gong, S.: Gait recognition without subject cooperation. Pattern Recognition Letters 31, 2052–2060 (2010)CrossRefGoogle Scholar
  7. 7.
    Zhang, E., Zhao, Y., Xiong, W.: Active Energy Image plus 2DLPP for gait recognition. Signal Processing 90, 2295–2302 (2010)CrossRefzbMATHGoogle Scholar
  8. 8.
    Yogarajah, P., Condell, J., Prasad, G.: PRWGEI: Poisson random walk based gait recognition. In: 7th International Symposium on Image and Signal Processing and Analysis (ISPA), pp. 662–667 (2011)Google Scholar
  9. 9.
    Huang, X., Boulgouris, N.: Gait recognition with Shifted Energy Image and structural feature extraction. IEEE Transactions on Image Processing 21, 2256–2268 (2012)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Wang, C., Zhang, J., Wang, L., Pu, J., Yuan, X.: Human identification using temporal information preserving gait template. IEEE Transactions on Pattern Analysis and Machine Intelligence 34, 2164–2176 (2012)CrossRefGoogle Scholar
  11. 11.
    Li, X., Chen, Y.: Gait recognition based on Structural Gait Energy Image. Journal of Computational Information Systems 9, 121–126 (2013)Google Scholar
  12. 12.
    Li, N., Xu, Y., Yang, X.: Part-based human gait identification under clothing and carrying condition variations. In: International Conference on Machine Learning and Cybernetics (ICMLC), vol. 1, pp. 268–273 (2010)Google Scholar
  13. 13.
    Yu, S., Tan, D., Tan, T.: A framework for evaluating the effect of view angle, clothing and carrying condition on gait recognition. In: 18th International Conference on Pattern Recognition (ICPR), vol. 4, pp. 441–444 (2006)Google Scholar
  14. 14.
    Zheng, S., Zhang, J., Huang, K., He, R., Tan, T.: Robust view transformation model for gait recognition. In: 18th IEEE International Conference on Image Processing (ICIP), pp. 2073–2076 (2011)Google Scholar
  15. 15.
    Lee, L., Grimson, W.: Gait analysis for recognition and classification. In: Proceedings of the 5th IEEE International Conference on Automatic Face and Gesture Recognition, pp. 148–155 (2002)Google Scholar
  16. 16.
    Dockstader, S., Berg, M., Tekalp, A.: Stochastic kinematic modeling and feature extraction for gait analysis. IEEE Transactions on Image Processing 12, 962–976 (2003)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Yoo, J., Nixon, M.: Automated markerless analysis of human gait motion for recognition and classification. ETRI Journal 33, 259–266 (2011)CrossRefGoogle Scholar
  18. 18.
    Dempster, W., Gaughran, G.: Properties of body segments based on size and weight. American Journal of Anatomy 120, 33–54 (1967)CrossRefGoogle Scholar
  19. 19.
    Drillis, R., Contini, R.: Body segment parameters. Office of Vocational Rehabilitation, Department of Health, Education and Welfare, New York, Report No. 1163.03 (1966)Google Scholar
  20. 20.
    Han, J., Bhanu, B.: Individual recognition using Gait Energy Image. IEEE Transactions on Pattern Analysis and Machine Intelligence 28, 316–322 (2006)CrossRefGoogle Scholar
  21. 21.
    Martín-Félez, R., Xiang, T.: Gait recognition by ranking. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part I. LNCS, vol. 7572, pp. 328–341. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  22. 22.
    Bashir, K., Xiang, T., Gong, S.: Gait recognition using Gait Entropy Image. In: 3rd International Conference on Crime Detection and Prevention (ICDP), pp. 1–6 (2009)Google Scholar
  23. 23.
    van der Maaten, L.: Matlab toolbox for dimensionality reductionGoogle Scholar
  24. 24.
    Hofmann, M., Bachmann, S., Rigoll, G.: 2.5D gait biometrics using the Depth Gradient Histogram Energy Image. In: 5th IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), pp. 399–403 (2012)Google Scholar
  25. 25.
    Hofmann, M., Geiger, J., Bachmann, S., Schuller, B., Rigoll, G.: The TUM gait from audio, image and depth (GAID) database: multimodal recognition of subjects and traits. Journal of Visual Communication and Image Representation (in press, 2013)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Tenika P. Whytock
    • 1
  • Alexander Belyaev
    • 1
  • Neil M. Robertson
    • 1
  1. 1.Institute of Sensors, Signals and Systems, School of Engineering & Physical SciencesHeriot-Watt UniversityEdinburghScotland, UK

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