Technology of Graphic & Image
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3184-3187,3192

Multi manifold discriminant analysis based on kernel sparse representation

Yang Yang1
Wang Zhengqun1
Xu Chunlin2
Ju Ling1
1. School of Information Engineering, Yangzhou University, Yangzhou Jiangsu 225127, China
2. Dept. of Technology, North Laser Technology Group Company Limited, Yangzhou Jiangsu 225009, China

Abstract

Aiming at the problem of non-linear separability in single sample face recognition, this paper proposed a multi manifold discriminant analysis based on kernel sparse representation(KSRMMDA) algorithm. Firstly, it divided the data image into blocks and established the multi-manifold model. Secondly, it used the method of kernel sparse representation to depict the relationship among data points of manifolds, and learned the intra-manifold graphs and inter-manifold graphs. Thirdly, it found the best projections in each manifold space to maintain the characteristics of the intra-manifold graph while suppressed the characteristics of the inter-manifold graph. Finally, it calculated the distance from the test sample manifold for classification and identification. Experiments on Extended Yale B and CMU PIE datasets show that the proposed algorithm is more robust to illumination and occlusion changes than other algorithms.

Foundation Support

国家自然科学基金资助项目(61803330)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.04.0135
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 10
Section: Technology of Graphic & Image
Pages: 3184-3187,3192
Serial Number: 1001-3695(2020)10-062-3184-04

Publish History

[2020-10-05] Printed Article

Cite This Article

杨洋, 王正群, 徐春林, 等. 基于核稀疏表示的多流形判别分析 [J]. 计算机应用研究, 2020, 37 (10): 3184-3187,3192. (Yang Yang, Wang Zhengqun, Xu Chunlin, et al. Multi manifold discriminant analysis based on kernel sparse representation [J]. Application Research of Computers, 2020, 37 (10): 3184-3187,3192. )

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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.

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