Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/70388
DC Field | Value | |
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dc.title | Frontal view-based gait identification using largest lyapunov exponents | |
dc.contributor.author | Lee, T.K.M. | |
dc.contributor.author | Ranganath, S. | |
dc.contributor.author | Sanei, S. | |
dc.date.accessioned | 2014-06-19T03:11:36Z | |
dc.date.available | 2014-06-19T03:11:36Z | |
dc.date.issued | 2006 | |
dc.identifier.citation | 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. | |
dc.identifier.isbn | 142440469X | |
dc.identifier.issn | 15206149 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/70388 | |
dc.description.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. | |
dc.source | Scopus | |
dc.type | Conference Paper | |
dc.contributor.department | ELECTRICAL & COMPUTER ENGINEERING | |
dc.description.sourcetitle | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings | |
dc.description.volume | 2 | |
dc.description.page | II173-II176 | |
dc.description.coden | IPROD | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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