Abstract：In low-resolution face recognition, the feature representation ability is not robust and the discrimination result of open-set face recognition is inaccurate. Therefore, an algorithm for low-resolution face recognition based on recursive label propagation algorithm is proposed. Firstly, VGG network is utilized to extract face representations. Secondly, the mapping relationship between high-resolution and low-resolution images can be acquired based on the similarity of feature vectors. Finally, the iteration label propagation algorithm is conducted on the labeled and unlabeled facial samples. During the iterations, the adaptive confidence threshold approaching to 100% recognition accuracy is estimated according to the confidence histogram of each category. The identified unlabeled samples are updated to the labeled sample set based on the threshold, thereby the recognition recall rate is improved. Experimental results on public face datasets show that the proposed algorithm achieves a high recall rate with 100% precision.
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