Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/29514
Title: Face feature extraction and recognition based on discriminant subclass-center manifold preserving projection
Authors: Jing, XY
Lan, C
Zhang, D 
Yang, JY
Li, M
Li, S
Zhu, SH
Keywords: Discriminant SMPP (DSMPP)
Dual-objective optimization
Face recognition
Manifold learning
Subclass discriminant analysis
Subclass-center manifold preserving projection (SMPP)
Issue Date: 2012
Publisher: North-Holland
Source: Pattern recognition letters, 2012, v. 33, no. 6, p. 709-717 How to cite?
Journal: Pattern recognition letters 
Abstract: Manifold learning is an effective dimensional reduction technique for face feature extraction, which, generally speaking, tends to preserve the local neighborhood structures of given samples. However, neighbors of a sample often comprise more inter-class data than intra-class data, which is an undesirable effect for classification. In this paper, we address this problem by proposing a subclass-center based manifold preserving projection (SMPP) approach, which aims at preserving the local neighborhood structure of subclass-centers instead of given samples. We theoretically show from a probability perspective that, neighbors of a subclass-center would comprise of more intra-class data than inter-class data, and thus is more desirable for classification. In order to take full advantage of the class separability, we further propose the discriminant SMPP (DSMPP) approach, which incorporates the subclass discriminant analysis (SDA) technique to SMPP. In contrast to related discriminant manifold learning methods, DSMPP is formulated as a dual-objective optimization problem and we present analytical solution to it. Experimental results on the public AR, FERET and CAS-PEAL face databases demonstrate that the proposed approaches are more effective than related manifold learning and discriminant manifold learning methods in classification performance.
URI: http://hdl.handle.net/10397/29514
ISSN: 0167-8655
EISSN: 1872-7344
DOI: 10.1016/j.patrec.2012.01.001
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