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Applied Intelligence

, Volume 43, Issue 4, pp 722–731 | Cite as

Penalized collaborative representation based classification for face recognition

  • Wei HuangEmail author
  • Xiaohui Wang
  • Zhong Jin
  • Jianzhong Li
Article

Abstract

The collaborative representation classification (CRC) exhibits superiority in both accuracy and computational efficiency. However, when representing the test sample by a linear combination of the training samples, the CRC does not account for the following: the probability of the test sample being from the same class as the training sample far from it is small. In this paper, we propose the algorithm, Penalized Collaborative Representation (PCR), which first uses the original collaborative representation to compute the distance between each training and test sample, and then treats these distances as penalized coefficients to design the penalized collaborative representation. The experimental results on multiple face databases show that our classifier, designed according PCR, has a very satisfactory classification performance.

Keywords

Face recognition Penalized collaborative representation Sparse representation Classification 

Notes

Acknowledgments

This work is partially supported by National Natural Science Foundation of China under Grant Nos. 61373063, 61233011, 61125305, 61375007, 61220301, and by National Basic Research Program of China under Grant No. 2014CB349303, and supported by the 2013 Higher School Discipline and Specialty Construction Project in Guangdong Province (2013LYM 0055 and 2013KJCX0127).

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Wei Huang
    • 1
    • 2
    Email author
  • Xiaohui Wang
    • 2
  • Zhong Jin
    • 1
  • Jianzhong Li
    • 3
  1. 1.School of Computer Science and EngineeringNanjing University of Science and TechnologyNanjingChina
  2. 2.Department of Computer Science and EngineeringHanshan Normal UniversityChaozhouChina
  3. 3.Department of Mathematics and StaticsHanshan Normal UniversityChaozhouChina

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