Producing virtual face images for single sample face recognition |
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Authors: | Tao Zhang Xianfeng Li Rong-Zuo Guo |
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Institution: | 1. Engineering Lab on Intelligent Perception for Internet of Things (ELIP), School of Electronic and Computer Engineering, Peking University, Shenzhen, China;2. Department of Computer Science, Sichuan Normal University, Chengdu 610068, China |
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Abstract: | For single sample face recognition, there are limited training samples, so the traditional face recognition methods are not applicable to this problem. In this paper we propose to combine two methods to produce virtual face images for single sample face recognition. We firstly use a symmetry transform to produce symmetrical face images. We secondly use the linear combination of two samples to generate virtual samples. As a result, we convert the special single sample problem into a non-single sample problem. We then use the 2DPCA method to extract features from the samples and use the nearest neighbor classifier to perform classification. Experimental results show that the proposed method can effectively improve the recognition rate of single sample face recognition. |
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Keywords: | Single sample Face recognition Symmetrical face Linear combination |
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