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DC Field | Value | Language |
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dc.contributor.author | Li, Y | - |
dc.contributor.author | Gong, S | - |
dc.contributor.author | Liddell, H | - |
dc.date.accessioned | 2017-02-24T10:48:47Z | - |
dc.date.available | 2001 | - |
dc.date.available | 2017-02-24T10:48:47Z | - |
dc.date.issued | 2001 | - |
dc.identifier.citation | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 8-14 December, 2001, Hawaii, USA, 2: pp. 258 - 263, (2001) | en_US |
dc.identifier.isbn | 0-7695-1272-0 | - |
dc.identifier.issn | 1063-6919 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/14120 | - |
dc.description.abstract | Recognising face with large pose variation is more challenging than that in a fixed view, e.g. frontal-view, due to the severe non-linearity caused by rotation in depth, self-shading and self-occlusion. To address this problem, a multi-view dynamic face model is designed to extract the shape-and-pose-free facial texture patterns from multi-view face images. Kernel Discriminant Analysis is developed to extract the significant non-linear discriminating features which maximise the between-class variance and minimise the within-class variance. By using the kernel technique, this process is equivalent to a Linear Discriminant Analysis in a high-dimensional feature space which can be solved conveniently. The identity surfaces are then constructed from these non-linear discriminating features. Face recognition can be performed dynamically from an image sequence by matching an object trajectory and model trajectories on the identity surfaces. | en_US |
dc.format.extent | 258 - 263 | - |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.source | IEEE Conference on Computer Vision and Pattern Recognition | - |
dc.source | IEEE Conference on Computer Vision and Pattern Recognition | - |
dc.subject | Face recognition | en_US |
dc.subject | Feature extraction | en_US |
dc.subject | Linear discriminant analysis | en_US |
dc.subject | Principal component analysis | en_US |
dc.title | Constructing facial identity surfaces in a nonlinear discriminating space | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.doi | http://dx.doi.org/10.1109/CVPR.2001.990969 | - |
pubs.volume | 2 | - |
Appears in Collections: | Dept of Computer Science Research Papers |
Files in This Item:
File | Description | Size | Format | |
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FullText.pdf | 308.39 kB | Adobe PDF | View/Open |
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