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Using the original and ‘symmetrical face’ training samples to perform representation based two-step face recognition
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资源说明：A limited number of available training samples have become one bottleneck of face recognition. In realworld applications, the face image might have various changes owing to varying illumination, facial
expression and poses. However, non-sufficient training samples cannot comprehensively convey these
possible changes, so it is hard to improve the accuracy of face recognition. In this paper, we propose to
exploit the symmetry of the face to generate new samples and devise a repre
expression and poses. However, non-sufficient training samples cannot comprehensively convey these
possible changes, so it is hard to improve the accuracy of face recognition. In this paper, we propose to
exploit the symmetry of the face to generate new samples and devise a repre
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