Human identification from video using advanced gait recognition techniques
Sivapalan, Sabesan (2014) Human identification from video using advanced gait recognition techniques. PhD thesis, Queensland University of Technology.
The solutions proposed in this thesis contribute to improve gait recognition performance in practical scenarios that further enable the adoption of gait recognition into real world security and forensic applications that require identifying humans at a distance. Pioneering work has been conducted on frontal gait recognition using depth images to allow gait to be integrated with biometric walkthrough portals. The effects of gait challenging conditions including clothing, carrying goods, and viewpoint have been explored. Enhanced approaches are proposed on segmentation, feature extraction, feature optimisation and classification elements, and state-of-the-art recognition performance has been achieved. A frontal depth gait database has been developed and made available to the research community for further investigation. Solutions are explored in 2D and 3D domains using multiple images sources, and both domain-specific and independent modality gait features are proposed.
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|Item Type:||QUT Thesis (PhD)|
|Supervisor:||Fookes, Clinton, Sridharan, Sridha, & Denman, Simon|
|Keywords:||human identification, gait recognition, biometric, sparse representation, discriminant analyses, gait energy image, local directional pattern, Microsoft Kinect, segmentation, 3D reconstruction|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > Institutes > Institute for Future Environments
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Institution:||Queensland University of Technology|
|Deposited On:||04 Nov 2014 04:00|
|Last Modified:||02 Sep 2015 06:03|
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