Weighted Neighbourhood Preserving Embedding in face recognition


Teoh, Andrew Beng Jin and Pang, Ying Han and Lim, Heng Siong (2010) Weighted Neighbourhood Preserving Embedding in face recognition. In: 2010 5th IEEE Conference on Industrial Electronics and Applications. IEEE Xplore, pp. 295-300. ISBN 978-1-4244-5045-9

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Graph Embedding (GE) along with its linearization outperforms the traditional linear dimension reduction techniques in face recognition, but there is still room for improvement on GE. This paper proposes an eigenvector weighting technique for a realization of linear GE, namely Neighbourhood Preserving Embedding (NPE) in face verification. The proposed method is called Eigenvector Weighting Function - NPE (EWF-NPE). The eigenspace is decomposed into three subspaces: (1) a subspace that is attributed to facial intra-class variations, (2) a subspace comprises of intrinsic facial characteristics, and (3) a subspace that is attributed to sensor and other external noises. Eigenfeatures are weighted differently in these subspaces. The proposed EWF-NPE ensures that only stable face subspace which yields informative data is emphasized, while the other two noise subspaces are deemphasized. Experimental investigations on FRGC and FERET databases demonstrate promising results of the proposed method.

Item Type: Book Section
Uncontrolled Keywords: Face recognition, graph embedding, weighting trick, Neighbourhood Preserving Embedding, subspace decomposition
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Engineering and Technology (FET)
Faculty of Information Science and Technology (FIST)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 24 Dec 2013 02:23
Last Modified: 05 Jan 2017 04:43
URII: http://shdl.mmu.edu.my/id/eprint/4656


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