Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/70388
Title: Frontal view-based gait identification using largest lyapunov exponents
Authors: Lee, T.K.M.
Ranganath, S. 
Sanei, S.
Issue Date: 2006
Source: Lee, T.K.M.,Ranganath, S.,Sanei, S. (2006). Frontal view-based gait identification using largest lyapunov exponents. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings 2 : II173-II176. ScholarBank@NUS Repository.
Abstract: This paper features two novel approaches to gait recognition; one is frontal motion analysis, using a single camera. This allows the use of other biometrics easily. Second is analysing gait using of nonlinear dynamics of time series, normally used in chaos theory, for classification. A set of point light sources attached to various points of a walking person allows the walker to be identified. Phase-space analysis of trajectories of these Moving Light Displays (MLDs) provides sufficient information for identification of people by their gait. Using chaotic measures to identify humans by their gait sets a significant precedent. © 2006 IEEE.
Source Title: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/70388
ISBN: 142440469X
ISSN: 15206149
Appears in Collections:Staff Publications

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