Abstract
In the face recognition system on campus, the influence of time and age change on face features can be neglected. This paper proposes a dimension reduction algorithm based on principal component analysis (PCA) algorithm and local binary patterns (LBP), and it is applied to campus face recognition APP. It is proved that the algorithm can significantly improve the speed and ensure its recognition accuracy in the application of small changes in the face and has certain reference value for practical application.
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Acknowledgements
This work was supported by Application-oriented Special Disciplines Double First-Class University Project of Hunan Province (Xiangjiaotong [2018] 469), Hunan University Students’ Research Learning and Innovative Experiment Project (Hunan Education Tong [2018] 255:750) and National Innovation and Entrepreneurship Training Program for College Students (201810546007).
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Li, K., Nie, R. (2021). Research on Face Recognition Algorithms and Application Based on PCA Dimension Reduction and LBP. In: Liu, Q., Liu, X., Li, L., Zhou, H., Zhao, HH. (eds) Proceedings of the 9th International Conference on Computer Engineering and Networks . Advances in Intelligent Systems and Computing, vol 1143. Springer, Singapore. https://doi.org/10.1007/978-981-15-3753-0_45
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DOI: https://doi.org/10.1007/978-981-15-3753-0_45
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