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Face Recognition Based on HOG and Fast PCA Algorithm

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Proceedings of the Fourth Euro-China Conference on Intelligent Data Analysis and Applications (ECC 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 682))

Abstract

A new method of face recognition based on gradient direction histogram (HOG) features extraction and fast principal component analysis (PCA) algorithm is proposed to solve the problem of low accuracy of face recognition under non-restrictive conditions. In this method, the Haar feature classifier is used to extract and extract the original data, and then the HOG features are extracted from the image data and the PCA dimension reduction is processed, and the Support Vector Machines (SVM) algorithm is used to recognize the face. The experimental results of the classification recognition on the LFW face database verify the effectiveness of the method.

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Acknowledgements

This research was supported in part by grants from the National Natural Science Foundation of China (No. 61402367). The authors gratefully thank Pro. Xiao-Qiang XI for his warmhearted discussion.

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Authors and Affiliations

  1. School of Communication and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an, 710061, China

    Xiang-Yu Li & Zhen-Xian Lin

Authors
  1. Xiang-Yu Li
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  2. Zhen-Xian Lin
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Correspondence to Xiang-Yu Li .

Editor information

Editors and Affiliations

  1. Department of Computer Science, VŠB-Technical University of Ostrava , Ostrava-Poruba, Czech Republic

    Pavel Krömer

  2. Dept. Lenguajes y Ciencias de la Computación, University of Málaga, Málaga, Spain

    Enrique Alba

  3. Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

  4. Department of Computer Science, VŠB-Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Václav Snášel

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Li, XY., Lin, ZX. (2018). Face Recognition Based on HOG and Fast PCA Algorithm. In: Krömer, P., Alba, E., Pan, JS., Snášel, V. (eds) Proceedings of the Fourth Euro-China Conference on Intelligent Data Analysis and Applications. ECC 2017. Advances in Intelligent Systems and Computing, vol 682. Springer, Cham. https://doi.org/10.1007/978-3-319-68527-4_2

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  • DOI: https://doi.org/10.1007/978-3-319-68527-4_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68526-7

  • Online ISBN: 978-3-319-68527-4

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