Weighted neighbourhood preserving embedding in face recognition

Andrew Beng Jin Teoh, Pang Ying Han, Lim Heng Siong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010
Pages295-300
Number of pages6
DOIs
Publication statusPublished - 2010 Sep 1
Event5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010 - Taichung, Taiwan, Province of China
Duration: 2010 Jun 152010 Jun 17

Publication series

NameProceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010

Other

Other5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010
CountryTaiwan, Province of China
CityTaichung
Period10/6/1510/6/17

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Teoh, A. B. J., Han, P. Y., & Siong, L. H. (2010). Weighted neighbourhood preserving embedding in face recognition. In Proceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010 (pp. 295-300). [5516836] (Proceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010). https://doi.org/10.1109/ICIEA.2010.5516836