Sparsity preserving projections with applications to face recognition

Dimensionality reduction methods (DRs) have commonly been used as a principled way to understand the high-dimensional data such as face images. In this paper, we propose a new unsupervised DR method called sparsity preserving projections (SPP). Unlike many existing techniques such as local preservin...

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Bibliographic Details
Published in:Pattern recognition 2010, Vol.43 (1), p.331-341
Main Authors: Qiao, Lishan, Chen, Songcan, Tan, Xiaoyang
Format: Article
Language:English
Subjects:
Applied sciences
Compressive sensing
Dimensionality reduction
Exact sciences and technology
Face recognition
Image processing
Information, signal and communications theory
Pattern recognition
Signal and communications theory
Signal processing
Signal representation. Spectral analysis
Signal, noise
Sparse representation
Telecommunications and information theory
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Summary:Dimensionality reduction methods (DRs) have commonly been used as a principled way to understand the high-dimensional data such as face images. In this paper, we propose a new unsupervised DR method called sparsity preserving projections (SPP). Unlike many existing techniques such as local preserving projection (LPP) and neighborhood preserving embedding (NPE), where local neighborhood information is preserved during the DR procedure, SPP aims to preserve the sparse reconstructive relationship of the data, which is achieved by minimizing a L1 regularization-related objective function. The obtained projections are invariant to rotations, rescalings and translations of the data, and more importantly, they contain natural discriminating information even if no class labels are provided. Moreover, SPP chooses its neighborhood automatically and hence can be more conveniently used in practice compared to LPP and NPE. The feasibility and effectiveness of the proposed method is verified on three popular face databases (Yale, AR and Extended Yale B) with promising results.
ISSN:0031-3203
1873-5142
DOI:10.1016/j.patcog.2009.05.005