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Proceedings Paper

Face recognition method based on SVM and SRC
Author(s): Chongyang Gao; Hongjuan Zhu; Lihua Liao
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Paper Abstract

For face recognition with global features, Support Vector Machines (SVM) and Sparse Representation Classification (SRC) are two methods which are difficult to take into account the recognition effect and efficiency when used alone. Based on the study of the two methods, this paper proposes a global linear face recognition method which combines Support Vector Machines and Sparse Representation Classification. On account of the recognition error of SVM, Sparse representation model is solved by Augmented Lagrange Multiplier method and the second recognition is carried out. In addition, the results on YALE show that this method can significantly improve the accuracy and speed of recognition.

Paper Details

Date Published: 14 August 2019
PDF: 7 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111791Q (14 August 2019); doi: 10.1117/12.2539669
Show Author Affiliations
Chongyang Gao, Shanghai Inspection and Testing Institute of Instruments and Automatic Systems Co., Ltd. (China)
Hongjuan Zhu, East China Univ. of Science and Technology (China)
Lihua Liao, Shanghai Inspection and Testing Institute of Instruments and Automatic Systems Co., Ltd (China)


Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

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