Abstract
Gait has received substantial attention from researchers. Different from other biometrics, gait can be captured in a distance and it is difficult to disguise. In this paper, we propose a feature template: Silhouette Spatio-temporal (SStS). It generates by concatenating silhouette projection vectors (SPV) which is formulated by projection of silhouette in vertical direction. We applied the Principle Component Analysis (PCA) for dimension reduction of the input feature space for recognition. The proposed algorithm has a promising performance, the identification rate is 95% in SOTON dataset and 90% CASIA dataset. Experiments showed that SStS has a high discriminative power and it is suitable for real-time gait recognition system.
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© 2005 Springer-Verlag Berlin Heidelberg
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Lam, T.H.W., Ieong, T.W.H.A., Lee, R.S.T. (2005). Silhouette Spatio-temporal Spectrum (SStS) for Gait-Based Human Recognition. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Image Analysis. ICAPR 2005. Lecture Notes in Computer Science, vol 3687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552499_35
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DOI: https://doi.org/10.1007/11552499_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28833-6
Online ISBN: 978-3-540-31999-3
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