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Eigenvector Weighting Function in Face Recognition
Joint Authors
Heng Siong, Lim
Ying Han, Pang
Jin, Andrew Teoh Beng
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-03-06
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Graph-based subspace learning is a class of dimensionality reduction technique in face recognition.
The technique reveals the local manifold structure of face data that hidden in the image space via a linear projection.
However, the real world face data may be too complex to measure due to both external imaging noises and the intra-class variations of the face images.
Hence, features which are extracted by the graph-based technique could be noisy.
An appropriate weight should be imposed to the data features for better data discrimination.
In this paper, a piecewise weighting function, known as Eigenvector Weighting Function (EWF), is proposed and implemented in two graph based subspace learning techniques, namely Locality Preserving Projection and Neighbourhood Preserving Embedding.
Specifically, the computed projection subspace of the learning approach is decomposed into three partitions: a subspace due to intra-class variations, an intrinsic face subspace, and a subspace which is attributed to imaging noises.
Projected data features are weighted differently in these subspaces to emphasize the intrinsic face subspace while penalizing the other two subspaces.
Experiments on FERET and FRGC databases are conducted to show the promising performance of the proposed technique.
American Psychological Association (APA)
Ying Han, Pang& Jin, Andrew Teoh Beng& Heng Siong, Lim. 2011. Eigenvector Weighting Function in Face Recognition. Discrete Dynamics in Nature and Society،Vol. 2011, no. 2011, pp.1-15.
https://search.emarefa.net/detail/BIM-478391
Modern Language Association (MLA)
Ying Han, Pang…[et al.]. Eigenvector Weighting Function in Face Recognition. Discrete Dynamics in Nature and Society No. 2011 (2011), pp.1-15.
https://search.emarefa.net/detail/BIM-478391
American Medical Association (AMA)
Ying Han, Pang& Jin, Andrew Teoh Beng& Heng Siong, Lim. Eigenvector Weighting Function in Face Recognition. Discrete Dynamics in Nature and Society. 2011. Vol. 2011, no. 2011, pp.1-15.
https://search.emarefa.net/detail/BIM-478391
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-478391