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D\(^{2}\)PLS: A Novel Bilinear Method for Facial Feature Fusion

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Book cover Neural Information Processing (ICONIP 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1142))

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Abstract

Two-dimensional partial least squares (2DPLS) is an effective two-view data analysis technique. However, conventional 2DPLS only takes into account the column information of two-dimensional images. In this paper, we simultaneously consider the column-wise and row-wise information of two-dimensional face images. We first propose a row-based two-dimensional PLS (r2DPLS) approach and then further present a novel double-directional PLS (D\(^{2}\)PLS) method. The proposed D\(^{2}\)PLS method can be optimized by two eigenvalue subproblems. Experimental results on the AR, Yale, and AT&T face databases show that our D\(^{2}\)PLS method can overall achieve better recognition accuracy than existing related methods.

Supported by Undergraduate Education and Teaching Reform Project of Yangzhou University under Grant YZUJX2016-32C; National Natural Science Foundation of China under Grants 61402203, 61703362, and 61611540347; Natural Science Foundation of Jiangsu Province of China under Grants BK20161338 and BK20170513; Yangzhou Science Project Fund of China under Grants YZ2016238 and YZ2017292; Excellent Young Backbone Teacher (Qing Lan) Project and Scientific Innovation Project Fund of Yangzhou University of China under Grant 2017CXJ033.

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Authors and Affiliations

  1. School of Information Engineering, Yangzhou University, Yangzhou, China

    Yun-Hao Yuan, Li Zhu, Yun Li, Jipeng Qiang & Bin Li

  2. School of Computer Science and Technology, Fudan University, Shanghai, China

    Yun-Hao Yuan

  3. School of Computer Science, Jiangsu University, Zhenjiang, China

    Jianping Gou

  4. Institute of Logistics Engineering, Shanghai Maritime University, Shanghai, China

    Chaofeng Li

Authors
  1. Yun-Hao Yuan
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  2. Li Zhu
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  3. Yun Li
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  4. Jipeng Qiang
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  5. Bin Li
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  6. Jianping Gou
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  7. Chaofeng Li
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Corresponding author

Correspondence to Yun-Hao Yuan .

Editor information

Editors and Affiliations

  1. Australian National University, Canberra, ACT, Australia

    Tom Gedeon

  2. Murdoch University, Murdoch, WA, Australia

    Kok Wai Wong

  3. Kyungpook National University, Daegu, Korea (Republic of)

    Minho Lee

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Yuan, YH. et al. (2019). D\(^{2}\)PLS: A Novel Bilinear Method for Facial Feature Fusion. In: Gedeon, T., Wong, K., Lee, M. (eds) Neural Information Processing. ICONIP 2019. Communications in Computer and Information Science, vol 1142. Springer, Cham. https://doi.org/10.1007/978-3-030-36808-1_44

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  • DOI: https://doi.org/10.1007/978-3-030-36808-1_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-36807-4

  • Online ISBN: 978-3-030-36808-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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