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Singular value decomposition-based virtual representation for face recognition

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Abstract

In the field of face recognition, a key issue is whether there are a sufficient number of face training samples with valid information. Due to the complexity of human face images, face recognition is easy to be affected by the external environment such as light intensity, gesture expression, hairstyle, and occlusion. Therefore, it is difficult to obtain enough effective samples in practical applications. In this paper, we propose a new algorithm that generates virtual images by utilizing the information of the test sample via singular value decomposition. The virtual images not only extend the training sample set but also can better adapt to the test sample. In addition, we use the weighted score fusion scheme to calculate the ultimate result, which can better take advantages of data from different sources including original images and virtual images. Experimental results on the Extended Yale_B, AR, GT, ORL, and FERET face databases prove that our algorithm can obtain satisfactory performance.

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Acknowledgments

This work is supported by the National Key R&D Program of China (No. 2017YFB1402102), the National Natural Science Foundation of China (Nos. 61873155, 61672333, 61703096, 11772178), the National Natural Science Foundation of Shaanxi Province (No. 2018JM6050), Transfer and Promotion Plan of Scientific and Technological Achievements of Shaanxi Province (No. 2019CGXNG-019), Innovation Chain of Key Industries of Shaanxi Province (No. 2019ZDLSF07-01), the Key Science and Technology Program of Shaanxi Province, China (No. 2016GY-081), the Fundamental Research Funds for the Central Universities (No. GK201803088), and the Ministry of Education Cooperation in Production and Education (No. 201701023062).

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Authors and Affiliations

  1. Key Laboratory of Modern Teaching Technology, Ministry of Education, Xi’an, 710062, China

    Shigang Liu, Yuhong Wang, Yali Peng, Keyou Zhang & Xiaojun Wu

  2. School of Computer Science, Shaanxi Normal University, Xi’an, 710119, China

    Shigang Liu, Yuhong Wang, Yali Peng, Keyou Zhang & Xiaojun Wu

  3. School of Information Science and Engineering, Shandong Normal University, Jinan, 250014, China

    Sujuan Hou

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  1. Shigang Liu
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Correspondence to Yali Peng.

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Liu, S., Wang, Y., Peng, Y. et al. Singular value decomposition-based virtual representation for face recognition. Machine Vision and Applications 31, 19 (2020). https://doi.org/10.1007/s00138-020-01067-4

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