Discriminant feature manifold for facial aging estimation

Fang, Hui, Grant, Phil and Chen, Min (2010) Discriminant feature manifold for facial aging estimation. International Conference on Pattern Recognition, 2010, Istanbul, Turkey, pp. 593-596, ISBN 978-1-4244-7542-1, ISSN 1051-4651, DOI https://doi.org/10.1109/ICPR.2010.150.

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Abstract

Computerised facial aging estimation, which has the potential for many applications in human-computer interactions, has been investigated by many computer vision researchers in recent years. In this paper, a feature-based discriminant subspace is proposed to extract more discriminating and robust representations for aging estimation. After aligning all the faces by a piece-wise affine transform, orthogonal locality preserving projection (OLPP) is employed to project local binary patterns (LBP) from the faces into an age-discriminant subspace. The feature extracted from this manifold is more distinctive for age estimation compared with the features using in the state-of-the-art methods. Based on the public database FG-NET, the performance of the proposed feature is evaluated by using two different regression techniques, quadratic function and neural-network regression. The proposed feature subspace achieves the best performance based on both types of regression.

Item Type: Conference or Workshop Item (Poster)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computing and Information Systems
Date Deposited: 28 Jan 2016 14:26
URI: http://repository.edgehill.ac.uk/id/eprint/6878

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