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Joint Subspace and Low-Rank Coding Method for Makeup Face Recognition

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  • Jianwei Lu
  • Guohua Zhou
  • Jiaqun Zhu
  • Lei Xue

Abstract

Facial makeup significantly changes the perceived appearance of the face and reduces the accuracy of face recognition. To adapt to the application of smart cities, in this study, we introduce a novel joint subspace and low-rank coding method for makeup face recognition. To exploit more discriminative information of face images, we use the feature projection technology to find proper subspace and learn a discriminative dictionary in such subspace. In addition, we use a low-rank constraint in the dictionary learning. Then, we design a joint learning framework and use the iterative optimization strategy to obtain all parameters simultaneously. Experiments on real-world dataset achieve good performance and demonstrate the validity of the proposed method.

Suggested Citation

  • Jianwei Lu & Guohua Zhou & Jiaqun Zhu & Lei Xue, 2021. "Joint Subspace and Low-Rank Coding Method for Makeup Face Recognition," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-8, April.
    • Handle: RePEc:hin:jnlmpe:9914452
    DOI: 10.1155/2021/9914452
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