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Asian Conference on Machine Learning

ACML 2009: Advances in Machine Learning pp 220–233Cite as

Coupled Metric Learning for Face Recognition with Degraded Images

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5828))

Abstract

Real-world face recognition systems are sometimes confronted with degraded face images, e.g., low-resolution, blurred, and noisy ones. Traditional two-step methods have limited performance, due to the disadvantageous issues of inconsistent targets between restoration and recognition, over-dependence on normal face images, and high computational complexity. To avoid these limitations, we propose a novel approach using coupled metric learning, without image restoration or any other preprocessing operations. Different from most previous work, our method takes into consideration both the recognition of the degraded test faces as well as the class-wise feature extraction of the normal faces in training set. We formulate the coupled metric learning as an optimization problem and solve it efficiently with a closed-form solution. This method can be generally applied to face recognition problems with various degrade images. Experimental results on various degraded face recognition problems show the effectiveness and efficiency of our proposed method.

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, China

    Bo Li

  2. Key Lab of Intelligent Information Processing, Chinese Academy of Sciences (CAS), Beijing, 100190, China

    Hong Chang, Shiguang Shan & Xilin Chen

  3. Institute of Computing Technology, CAS, Beijing, 100190, China

    Hong Chang, Shiguang Shan & Xilin Chen

Authors
  1. Bo Li
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  2. Hong Chang
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  3. Shiguang Shan
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  4. Xilin Chen
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Editor information

Editors and Affiliations

  1. National Laboratory for Novel Software Technology, Nanjing University, 22 Hankou Road, 210093, Nanjing, China

    Zhi-Hua Zhou

  2. The Institute of Scientific and Industrial Research, Osaka University, 8-1 Mihogaoka, 567, Osaka, Ibaraki, Japan

    Takashi Washio

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© 2009 Springer-Verlag Berlin Heidelberg

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Li, B., Chang, H., Shan, S., Chen, X. (2009). Coupled Metric Learning for Face Recognition with Degraded Images. In: Zhou, ZH., Washio, T. (eds) Advances in Machine Learning. ACML 2009. Lecture Notes in Computer Science(), vol 5828. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05224-8_18

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  • DOI: https://doi.org/10.1007/978-3-642-05224-8_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05223-1

  • Online ISBN: 978-3-642-05224-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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