Sparsity Preserving Discriminant Projections with Applications to Face Recognition
Joint Authors
Chen, Yufei
Zhao, Weidong
Wang, Zhicheng
Ren, Yingchun
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-01-20
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Dimensionality reduction is extremely important for understanding the intrinsic structure hidden in high-dimensional data.
In recent years, sparse representation models have been widely used in dimensionality reduction.
In this paper, a novel supervised learning method, called Sparsity Preserving Discriminant Projections (SPDP), is proposed.
SPDP, which attempts to preserve the sparse representation structure of the data and maximize the between-class separability simultaneously, can be regarded as a combiner of manifold learning and sparse representation.
Specifically, SPDP first creates a concatenated dictionary by classwise PCA decompositions and learns the sparse representation structure of each sample under the constructed dictionary using the least square method.
Secondly, a local between-class separability function is defined to characterize the scatter of the samples in the different submanifolds.
Then, SPDP integrates the learned sparse representation information with the local between-class relationship to construct a discriminant function.
Finally, the proposed method is transformed into a generalized eigenvalue problem.
Extensive experimental results on several popular face databases demonstrate the feasibility and effectiveness of the proposed approach.
American Psychological Association (APA)
Ren, Yingchun& Wang, Zhicheng& Chen, Yufei& Zhao, Weidong. 2016. Sparsity Preserving Discriminant Projections with Applications to Face Recognition. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1112296
Modern Language Association (MLA)
Ren, Yingchun…[et al.]. Sparsity Preserving Discriminant Projections with Applications to Face Recognition. Mathematical Problems in Engineering No. 2016 (2016), pp.1-12.
https://search.emarefa.net/detail/BIM-1112296
American Medical Association (AMA)
Ren, Yingchun& Wang, Zhicheng& Chen, Yufei& Zhao, Weidong. Sparsity Preserving Discriminant Projections with Applications to Face Recognition. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1112296
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112296