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Local descriptor margin projections (LDMP) for face recognition

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Abstract

Feature extraction is a key problem in face recognition systems. This paper tackles this problem by combining the strength of image descriptor with dimensionality reduction technology. So, this paper proposes a new efficient face recognition method-local descriptor margin projections (LDMP). Firstly, we propose a novel local descriptor for face image representation. At this step, an effective and simple metric approach named gray value accumulating distance (GAD) is firstly proposed. And then a novel local descriptor based on GAD is presented to capture the local structure information between central pixel and its neighbors effectively. Secondly, we propose a dimensionality reduction algorithm named maximum margin learning projections (MMLP) which can obtain the low-dimensional and discriminative feature. Finally, experimental results on the Yale, Extended Yale B, PIE, AR and LFW face databases show the effectiveness of the proposed method.

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Notes

  1. http://www.openu.ac.il/home/hassner/projects/Patchlbp/.

  2. http://users.soe.ucsc.edu/~milanfar/research/rokaf/.html/download_object.php.

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Acknowledgements

This work is supported by the National Natural Science Fund of China (Grant Nos. 61503195, 61462064, 61203243,61402231, 61603192 and 61272077), the Natural Science Fund of Jiangsu Province (Grant No. BK20161580), the University Natural Science Fund of Jiangsu Province of China (Grant No. 15KJB520018, 16KJB520020 and 12KJA63001), the Project Funded by China Postdoctoral Science Foundation (Grant No. 2016M600433), the Project Funded by PAPD and CICAEET, and the Project supported by the Jiangsu Key Laboratory of Image and Video Understanding for Social Safety (Nanjing University of Science and Technology) (Grant No. 30916014107).

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Authors and Affiliations

  1. School of Technology, Nanjing Audit University, Nanjing, 211815, China

    Zhangjing Yang, Minghua Wan, Fanlong Zhang, Guowei Yang & Jincheng Zhang

  2. School of Computer Science and Engineering, Southeast University, Nanjing, 210009, China

    Zhangjing Yang

  3. School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China

    Pu Huang

  4. Key Laboratory of Image and Video Understanding for Social Safety, Nanjing University of Science and Technology, Nanjing, 210094, China

    Pu Huang

  5. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Chengshan Qian

  6. Fujian Provincial Key Laboratory of Information Processing and Intelligent Control, Fuzhou, 350121, China

    Zhangjing Yang & Zuoyong Li

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  1. Zhangjing Yang
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  3. Minghua Wan
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Correspondence to Zhangjing Yang.

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Yang, Z., Huang, P., Wan, M. et al. Local descriptor margin projections (LDMP) for face recognition. Int. J. Mach. Learn. & Cyber. 9, 1387–1398 (2018). https://doi.org/10.1007/s13042-017-0652-1

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