Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/54893
Title: Silhouette Spatio-temporal Spectrum (SStS) for gait-based human recognition
Authors: Lam, T
Ao Ieong, T
Lee, RST
Issue Date: 2005
Publisher: Springer
Source: In S Singh, M Singh, C Apte & P Perner (Eds.), Pattern recognition and image analysis : Third International Conference on Advances in Pattern Recognition, ICAPR 2005, Bath, UK, August 22-25, 2005, Proceedings, Part II, p. 309-315. Berlin ; New York: Springer, 2005 How to cite?
Series/Report no.: Lecture notes in computer science ; v. 3687
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.
URI: http://hdl.handle.net/10397/54893
ISBN: 9783540287575 (pt. 1)
3540287574 (pt. 1)
9783540288336 (pt. 2)
3540288333 (pt. 2)
DOI: 10.1007/11552499_35
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