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The Realization of Face Recognition Algorithm Based on Compressed Sensing (Short Paper)

  • Huimin ZhangEmail author
  • Yan Sun
  • Haiwei Sun
  • Xin Yuan
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 268)

Abstract

Once the sparse representation-based classifier (SRC) was raised, it achieved a more outstanding performance than typical classification algorithm. Normally, SRC algorithm adopts \(l_1\)-norm minimization method to solve the sparse vector, and its computation complexity increases correspondingly. In this paper, we put forward a compressed sensing reconstruction algorithm based on residuals. This algorithm utilizes the local sparsity within figures as well as the non-local similarity among figure blocks to boost the performance of the reconstruction algorithm while remaining a median computation complexity. It achieves a superior recognition rate in the experiments of Yale facial database.

Keywords

Compressed sensing Face recognition Feature extraction Sparse representation classification Image reconstruction 

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  1. 1.University of MichiganAnn ArborUSA
  2. 2.Shanghai Jiao Tong UniversityShanghaiChina
  3. 3.Jiangsu UniversityZhenjiangChina

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