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Gender classification based on facial surface normals

Wu, Jing, Smith, W.A.P. and Hancock, E.R. 2008. Gender classification based on facial surface normals. Presented at: International Conference on Pattern Recognition, Tampa, FL., 8-11 Dec 2008. 19th International Conference on Pattern Recognition : (ICPR 2008) ; Tampa, Florida, USA 8-11 December 2008. Piscataway, N.J.: IEEE, pp. 1-4. 10.1109/ICPR.2008.4761056

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Abstract

In this paper, we perform gender classification based on 2.5D facial surface normals (facial needle-maps), and present two novel principal geodesic analysis (PGA) methods, weighted PGA and supervised PGA, to parameterize the facial needle-maps, and compare their performances with PGA for gender classification. Experimental results demonstrate the feasibility of gender classification based on facial needle-maps, and show that incorporating weights or pairwise relationships of labeled data into PGA improves the gender discriminating powers in the leading eigenvectors and the gender classification accuracy.

Item Type: Conference or Workshop Item (Paper)
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher: IEEE
ISBN: 9781424421749
ISSN: 1051-4651
Last Modified: 04 Jun 2017 09:03
URI: http://orca.cf.ac.uk/id/eprint/89868

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