Face recognition using virtual parametric eigenspace signatures

Graham, D. B. and Allinson, N. M. (1997) Face recognition using virtual parametric eigenspace signatures. In: Sixth International Conference on Image Processing and Its Applications, 1997, 14-17 July 1997, Dublin.

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Face recognition using virtual parametric eigenspace signatures
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Abstract

This paper proposes a novel system for face recognition which utilises the parametric eigenspace of Murase and Nayar (1993) to determine both the pose and identification of a face held within a current face database. In order that all views from profile to frontal are available for recognition a sample of views are taken from a range of angles so that, during the identification process, virtual views can be estimated from a novel view to supply ordered coordinates in the eigenvector subspace for the recognition algorithm. The method is demonstrated on a set of faces and results show that the technique is practical. The system is described in the context of a theoretical model of human face recognition which closely resembles that described in the literature

Item Type:Conference or Workshop Item (Paper)
Additional Information:This paper proposes a novel system for face recognition which utilises the parametric eigenspace of Murase and Nayar (1993) to determine both the pose and identification of a face held within a current face database. In order that all views from profile to frontal are available for recognition a sample of views are taken from a range of angles so that, during the identification process, virtual views can be estimated from a novel view to supply ordered coordinates in the eigenvector subspace for the recognition algorithm. The method is demonstrated on a set of faces and results show that the technique is practical. The system is described in the context of a theoretical model of human face recognition which closely resembles that described in the literature
Keywords:face recognition, algorithm, Eigenvectors, recognition algorithm
Subjects:G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
ID Code:5082
Deposited By: Tammie Farley
Deposited On:20 Apr 2012 18:58
Last Modified:13 Mar 2013 09:06

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