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Technology of Graphic & Image
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2851-2855,2865

Structured robust low-rank recovery algorithm for face recognition with mixed contaminations

Wu Xiaoyi
Wu Xiaojun
Chen Zhe
School of Internet of Things Engineering, Jiangnan University, Wuxi Jiangsu 214122, China

Abstract

When there exist mixed contaminations in face images, traditional low-rank recovery algorithms usually imposes only one constraint on the corresponding contaminations, it cannot recover clean samples very well. In order to solve this problem, this paper proposed a structured robust low-rank recovery algorithm(SRLRR). The SRLRR algorithm imposed low-rank constraint on the 2D error image to remove the continuous contamination, and introduced sparse constraint to separate the noise that obeyed the Laplacian distribution in samples. Moreover, the proposed algorithm imposed a block-diagonal structured constraint on the representation coefficient to learn the more discriminative low-rank representation. The experimental results on three commonly and using standard databases verify the effectiveness and robustness of the proposed SRLRR algorithm.

Foundation Support

国家自然科学基金资助项目(61672265,U1836218)
国家教育部111资助项目(B12018)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.04.0165
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 9
Section: Technology of Graphic & Image
Pages: 2851-2855,2865
Serial Number: 1001-3695(2020)09-060-2851-05

Publish History

[2020-09-05] Printed Article

Cite This Article

吴小艺, 吴小俊, 陈哲. 针对混合污染的结构化鲁棒低秩恢复算法在人脸识别中的应用 [J]. 计算机应用研究, 2020, 37 (9): 2851-2855,2865. (Wu Xiaoyi, Wu Xiaojun, Chen Zhe. Structured robust low-rank recovery algorithm for face recognition with mixed contaminations [J]. Application Research of Computers, 2020, 37 (9): 2851-2855,2865. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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