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Discriminant Feature Manifold for Facial Aging Estimation / Hui Fang, Phil Grant, Min Chen, Philip Grant

Pattern Recognition (ICPR), 2010 20th International Conference on, Volume: 23-26 Aug. 2010, Pages: 593 - 596

Swansea University Author: Philip Grant

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DOI (Published version): 10.1109/ICPR.2010.150

Abstract

<p>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...

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Published in: Pattern Recognition (ICPR), 2010 20th International Conference on
Published: 2010
URI: https://cronfa.swan.ac.uk/Record/cronfa5280
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Abstract: <p>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.</p>
College: College of Science
Start Page: 593
End Page: 596