Chinese Journal of Intelligent Science and Technology ›› 2021, Vol. 3 ›› Issue (3): 334-341.doi: 10.11959/j.issn.2096-6652.202134

• Special Issue: Intelligent Object Detection and Recognition • Previous Articles     Next Articles

Collaborative representation based classifier with maximum correntropy criterion and locality constraint

Qinru YU, Guifu LU   

  1. School of Computer and Information, Anhui Polytechnic University, Wuhu 241000, China
  • Revised:2021-07-19 Online:2021-09-15 Published:2021-09-01
  • Supported by:
    The National Natural Science Foundation of China(61976005);The National Natural Science Foundation of China(61772277);The Natural Science Foundation of Anhui Province(1908085MF183)

Abstract:

A method which utilizes maximum correntropy criterion and locality information called collaborative representation based classifier with maximum correntropy criterion and locality constraint (CRC/MCCLC) was proposed.On the one hand, CRC/MCCLC was not only more robust to outliers than L1 norm but also could be computed efficiently using half-quadratic optimization technique because of the use of maximum correntropy criterion.On the other hand, CRC/MCCLC could obtain more discriminative information from the training samples and could lead to an approximately sparse representation because of the use of locality information.Extensive experimental results on some image databases demonstrate that CRC/MCCLC can achieve the state-of-the-art performance on these image databases.

Key words: face recognition, collaborative representation, sparse representation, maximum correntropy criterion, locality constraint

CLC Number: 

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