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Ubiquitous single-sample face recognition under occlusion based on sparse representation with dual features

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Abstract

Face recognition has attracted numerous research interests as a promising biometrics with many distinct advantages. However there are inevitable gaps lying between face recognition in lab condition and ubiquitous face recognition application in real word, which mainly caused by various illumination condition, random occlusion, lack of sample images and etc. To combat the influence of these impact factors, a novel dual features based sparse representation classification algorithm is proposed. It contains illumination robust feature based dictionary learning and fused sparse representation with dual features. Firstly, an enhanced center-symmetric local binary pattern (ECSLBP) derived from conducting center symmetric encoding on the fused component images is presented for dictionary construction. Then, sparse representation with dual features including both ECSLBP and CSLBP is conducted. The final recognition is derived from the fusion of both classification results according to a novel fusion scheme. Numerous experiments results on both Extended Yale B database and the AR database show that the proposed algorithm exhibits distinguished discriminative ability and state-of-the-art recognition rate compared with other existing algorithms, especially for single sample face recognition under random partial occlusion.

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Acknowledgements

This work is supported by the National Key R&D Program of China under Grant 2017YFB0802300, National Natural Foundation of China (Grant No. 61503005), Research Project of Beijing Municipal Education Commission (Grant No. SQKM201810009005) and High Innovation Program of Beijing (2015000026833ZK04).

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Authors and Affiliations

  1. School of Computer Science, North China University of Technology, Beijing, China

    Chen Li, Shuai Zhao, Wei Song, Ke Xiao & Yanjie Wang

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  1. Chen Li
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  2. Shuai Zhao
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  3. Wei Song
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  4. Ke Xiao
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  5. Yanjie Wang
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Correspondence to Chen Li or Wei Song.

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Li, C., Zhao, S., Song, W. et al. Ubiquitous single-sample face recognition under occlusion based on sparse representation with dual features. J Ambient Intell Human Comput 15, 1493–1503 (2024). https://doi.org/10.1007/s12652-017-0604-3

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