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A New Method for Human Gait Recognition Using Temporal Analysis

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Computational Intelligence and Security (CIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3801))

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Abstract

Human gait recognition is the process of identifying individuals by their walking manners. The gait as one of newly coming biometrics has recently gained more and more interests from computer vision researchers. In this paper, we propose a new method for model-free recognition of gait based on silhouette in computer vision sequences. The silhouette shape is represented by a novel approach which includes not only the spatial body contour but also the temporal information. First, a background subtraction is used to separate objects from background. Then, we represent the spatial shape of walker and their motion by the temporal matrix, and use Discrete Fourier analysis to analyze the gait feature. The nearest neighbor classifier is used to distinguish the different gaits of human. The performance of our approach is tested using different gait databases. Recognition results show this approach is efficient.

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References

  1. Murary, M.P., Drought, A.B., Kory, R.C.: Walking Pattern of Movement. American Journal Medicine 46, 290–332 (1967)

    Google Scholar 

  2. Wang, L., Tan, T.N., Hu, W.M., Ning, H.Z.: Automatic Gait Recognition Based on Statistical Shape Analysis. IEEE Transactions on Image Processing 12, 1120–1131 (2003)

    Article  MathSciNet  Google Scholar 

  3. Niyogi, S.A., Adelson, E.H.: Analyzing and Recognizing Walking Figures in XYT. In: Computer Vision and Pattern Recognition 1994, Seattle, USA, pp. 469–474 (1994)

    Google Scholar 

  4. Little, J., Boyd, J.: Recognising People by Their Gait: The Shape of Motion. Videre 1, 1–32 (1998)

    Google Scholar 

  5. Wang, L., Tan, T.N., Ning, H.Z., Hu, W.M.: Silhouette Analysis-Based Gait Recognition for Human Identification. IEEE Transactions on Pattern Analysis and Machine Intelligence 25, 1505–1528 (2003)

    Article  Google Scholar 

  6. Hayfron-Acquah, J., Nixon, M.S., Carter, J.N.: Human identification by spatio-temporal symmetry. In: Proc. of Intl. Conf. on Pattern Recognition, Quebec, Canada, pp. 632–635 (2002)

    Google Scholar 

  7. Yam, C.Y., Nixon, M.S., Carter, J.N.: Extended model-based automatic gait recognition of walking and running. In: Bigun, J., Smeraldi, F. (eds.) AVBPA 2001. LNCS, vol. 2091, pp. 278–283. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  8. Cunado, D., Nixon, M.S., Carter, J.N.: Automatic Extraction and Description of Human Gait Models for Recognition Purposes. Computer Vision and Image Understanding 90, 1–41 (2003)

    Article  Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Su, H., Huang, F. (2005). A New Method for Human Gait Recognition Using Temporal Analysis. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_155

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  • DOI: https://doi.org/10.1007/11596448_155

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30818-8

  • Online ISBN: 978-3-540-31599-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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