Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/14382
Title: Recognising trajectories of facial identities using kernel discriminant analysis
Authors: Li, Y
Gong, S
Liddell, H
Issue Date: 2003
Publisher: Elsevier
Citation: Image and Vision Computing, pp. 613 - 622, (2003)
Abstract: We present a comprehensive approach to address three challenging problems in face recognition: modelling faces across multi-views, extracting the non-linear discriminating features, and recognising moving faces dynamically in image sequences. A multi-view dynamic face model is designed to extract the shape-and-pose-free facial texture patterns. Kernel Discriminant Analysis, which employs the kernel technique to perform Linear Discriminant Analysis in a high-dimensional feature space, is developed to extract the significant non-linear features which maximise the between-class variance and minimise the within-class variance. Finally, an identity surface based face recognition is performed dynamically from video input by matching object and model trajectories.
URI: http://bura.brunel.ac.uk/handle/2438/14382
Appears in Collections:Dept of Computer Science Research Papers

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