Name
Abstract | ||
|---|---|---|
Human recognition using gait features in predominantly frontal-normal motion has been described in this paper. Compared to current methods for gait identification, this allows convenient combination of other biometrics using a single camera. We analyse how this motion yields more dynamic information, allowing us to characterise gait in a new way, using nonlinear dynamics of time series normally used in chaos theory. Using chaotic measures to identify humans by their gait is a significant precedent. Phase-space analysis of trajectories of a set of Moving Light Displays (MLDs) provides sufficient information for identification of people by their gait. A number of experiments has been set up to demonstrate the viability of this approach which contribute to the relatively unexplored area of fusion of face with gait. This provides a more robust identification scheme. |
Year | Venue | Field |
|---|---|---|
2007 | European Signal Processing Conference | Computer vision,Facial recognition system,Nonlinear system,Identification scheme,Gait,Computer science,Artificial intelligence,Biometrics,Chaotic,Chaos theory,Trajectory |
DocType | ISBN | Citations |
Conference | 978-839-2134-04-6 | 1 |
PageRank | References | Authors |
0.41 | 5 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tracey Kah-mein Lee | 1 | 61 | 11.97 |
| Mohammed Belkhatir | 2 | 126 | 23.74 |
| Poh Aun Lee | 3 | 1 | 0.41 |
| Saeid Sanei | 4 | 530 | 72.63 |
| Kia-Fock Loe | 5 | 180 | 20.88 |