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Robust Tensor Preserving Projection for Multispectral Face Recognition
Joint Authors
Jin, Bo
Sun, Shaoyuan
Zhao, Haitao
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-12
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Multiple imaging modalities based face recognition has become a hot research topic.
A great number of multispectral face recognition algorithms/systems have been designed in the last decade.
How to extract features of different spectrum has still been an important issue for face recognition.
To address this problem, we propose a robust tensor preserving projection (RTPP) algorithm which represents a multispectral image as a third-order tensor.
RTPP constructs sparse neighborhoods and then computes weights of the tensor.
RTPP iteratively obtains one spectral space transformation matrix through preserving the sparse neighborhoods.
Due to sparse representation, RTPP can not only keep the underlying spatial structure of multispectral images but also enhance robustness.
The experiments on both Equinox and DHUFO face databases show that the performance of the proposed method is better than those of related algorithms.
American Psychological Association (APA)
Sun, Shaoyuan& Zhao, Haitao& Jin, Bo. 2014. Robust Tensor Preserving Projection for Multispectral Face Recognition. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-483879
Modern Language Association (MLA)
Sun, Shaoyuan…[et al.]. Robust Tensor Preserving Projection for Multispectral Face Recognition. Mathematical Problems in Engineering No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-483879
American Medical Association (AMA)
Sun, Shaoyuan& Zhao, Haitao& Jin, Bo. Robust Tensor Preserving Projection for Multispectral Face Recognition. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-483879
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-483879