Model-Free Gait-Based Human Recognition in Video

  • Bir Bhanu
  • Ju Han
Part of the Advances in Pattern Recognition book series (ACVPR)


In this chapter, the GEI-based general framework presented earlier is used for individual recognition in diverse scenarios.

Insufficient training data associated with an individual is a major problem in gait recognition due to the difficulty of the data acquisition. To address this issue, we not only compute real templates from training silhouette sequences directly, but also generate synthetic templates from training sequences by simulating silhouette distortion. Features learned from real templates characterize human walking properties provided in training sequences, and features learned from synthetic templates predict gait properties under other conditions. A feature fusion strategy is therefore applied at the decision level to improve recognition performance.


Feature Vector Training Sequence Bayesian Classifier Individual Recognition Human Activity Recognition 
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.


  1. 1.
    Abuelgasim, A., Fraser, R.: Day and night-time active fire detection over north America using NOAA-16 AVHRR data. In: Proceedings of IEEE International Geoscience and Remote Sensing Symposium, vol. 3, pp. 1489–1491 (2002) Google Scholar
  2. 5.
    Andreone, L., Antonello, P.C., Bertozzi, M., Broggi, A., Fascioli, A., Ranzato, D.: Vehicle detection and localization in infra-red images. In: Proceedings of IEEE International Conference on Intelligent Transportation Systems, pp. 141–146 (2002) Google Scholar
  3. 6.
    Arlowe, H.D.: Thermal detection contrast of human targets. In: Proceedings of IEEE International Carnahan Conference on Security Technology, pp. 27–33 (1992) Google Scholar
  4. 52.
    Ginesu, G., Giusto, D.D., Margner, V., Meinlschmidt, P.: Detection of foreign bodies in food by thermal image processing. IEEE Trans. Ind. Electron. 51(2), 480–490 (2004) CrossRefGoogle Scholar
  5. 59.
    Han, J., Bhanu, B.: Statistical feature fusion for gait-based human recognition. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 842–847 (2004) Google Scholar
  6. 67.
    Holland, J.A., Yan, X.-H.: Ocean thermal feature recognition, discrimination, and tracking using infrared satellite imagery. IEEE Trans. Geosci. Remote Sens. 30(5), 1046–1053 (1992) CrossRefGoogle Scholar
  7. 70.
    Hu, M.K.: Visual pattern recognition by moment invariants. IRE Trans. Inf. Theory 8, 179–187 (1962) MATHGoogle Scholar
  8. 72.
    Huang, P.S., Harris, C.J., Nixon, M.S.: Recognizing humans by gait via parametric canonical space. Artif. Intell. Eng. 13, 359–366 (1999) CrossRefGoogle Scholar
  9. 81.
    Kale, A., Chowdhury, A.K.R., Chellappa, R.: Towards a view invariant gait recognition algorithm. In: Proceedings of IEEE Conference on Advanced Video and Signal Based Surveillance, pp. 143–150 (2003) Google Scholar
  10. 85.
    Kale, A., Sundaresan, A., Rajagopalan, A.N., Cuntoor, N.P., Roy-Chowdhury, A.K., Kruger, V., Chellappa, R.: Identification of humans using gait. IEEE Trans. Image Process. 13(9), 1163–1173 (2004) CrossRefGoogle Scholar
  11. 91.
    Koza, J.: Genetic Programming II: Automatic Discovery of Reusable Programs. MIT Press, Cambridge (1994) MATHGoogle Scholar
  12. 106.
    Lin, Y., Bhanu, B.: Evolutionary feature synthesis for object recognition. IEEE Trans. Syst. Man Cybern., Part C 35(2), 156–171 (2005) CrossRefGoogle Scholar
  13. 107.
    Little, J.J., Boyd, J.E.: Recognizing people by their gait: the shape of motion. Videre, J. Comput. Vis. Res. 1(2), 1–32 (1998) Google Scholar
  14. 116.
    Martinez, P.L., van Kempen, L., Sahli, H., Ferrer, D.C.: Improved thermal analysis of buried landmines. IEEE Trans. Geosci. Remote Sens. 42(9), 1965–1975 (2004) CrossRefGoogle Scholar
  15. 121.
    Nadimi, S., Bhanu, B.: Physical models for moving shadow and object detection in video. IEEE Trans. Pattern Anal. Mach. Intell. 26(8), 1079–1087 (2004) CrossRefGoogle Scholar
  16. 132.
    Pavlidis, I., Levine, J., Baukol, P.: Thermal imaging for anxiety detection. In: Proceedings of IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications, pp. 104–109 (2000) Google Scholar
  17. 136.
    Pheasant, S.: Bodyspace: Anthropometry, Ergonomics and Design. Taylor & Francis, London (1986) Google Scholar
  18. 137.
    Phillips, P.J., Sarkar, S., Robledo, I., Grother, P., Bowyer, K.: The gait identification challenge problem: data sets and baseline algorithm. In: Proceedings of International Conference on Pattern Recognition, vol. 1, pp. 385–388 (2002) Google Scholar
  19. 144.
    Riggan, P.J., Hoffman, J.W.: Field applications of a multi-spectral, thermal imaging radiometer. In: Proceedings of IEEE Aerospace Conference, vol. 3, pp. 443–449 (1999) Google Scholar
  20. 150.
    Sarkar, S., Phillips, P.J., Liu, Z., Vega, I.R., Grother, P., Bowyer, K.W.: The humanid gait challenge problem: data sets, performance, and analysis. IEEE Trans. Pattern Anal. Mach. Intell. 27(2), 162–177 (2005) CrossRefGoogle Scholar
  21. 154.
    Shakhnarovich, G., Lee, L., Darrell, T.: Integrated face and gait recognition from multiple views. In: Proceedings of IEEE Workshop on Visual Motion, vol. 1, pp. 439–446 (2001) Google Scholar
  22. 157.
    Spencer, N., Carter, J.: Towards pose invariant gait reconstruction. In: Proceedings of IEEE International Conference on Image Processing, vol. 3, pp. 261–264 (2005) Google Scholar
  23. 166.
    Tolliver, D., Collins, R.T.: Gait shape estimation for identification. In: Proceedings of fourth International Conference on Audio- and Video-Based Biometric Person Authentication. LNCS, vol. 2688, pp. 734–742 (2003) Google Scholar
  24. 179.
    Wang, L., Tan, T., Hu, W., Ning, H.: Automatic gait recognition based on statistical shape analysis. IEEE Trans. Image Process. 12(9), 1120–1131 (2003) MathSciNetCrossRefGoogle Scholar
  25. 195.
    Yoshitomi, Y., Miyaura, T., Tomita, S., Kimura, S.: Face identification using thermal image processing. In: Proceedings of IEEE International Workshop on Robot and Human Communication, pp. 374–379 (1997) Google Scholar

Copyright information

© Springer-Verlag London Limited 2010

Authors and Affiliations

  1. 1.Bourns College of EngineeringUniversity of CaliforniaRiversideUSA
  2. 2.Lawrence Berkeley National LaboratoryUniversity of CaliforniaBerkeleyUSA

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