Noise-robust dictionary learning with slack block-Diagonal structure for face recognition

作者：

Highlights：

• We propose a slack block-diagonal (SBD) structure for representation where the target structure matrix is dynamically updated to instead of the strict ‘0-1’ structure.

• In order to depict the noise in face images more precisely, we also propose a robust dictionary learning algorithm based on mixed-noise model by utilizing the above SBD structure (SBD2L).

• Moreover, we add a low-rank constraint on the representation matrix to enhance the dictionary’s robustness to noise.

摘要

•We propose a slack block-diagonal (SBD) structure for representation where the target structure matrix is dynamically updated to instead of the strict ‘0-1’ structure.•In order to depict the noise in face images more precisely, we also propose a robust dictionary learning algorithm based on mixed-noise model by utilizing the above SBD structure (SBD2L).•Moreover, we add a low-rank constraint on the representation matrix to enhance the dictionary’s robustness to noise.

论文关键词：Face recognition,Low-rank representation,Noise-robust dictionary learning,Slack block-diagonal structure

论文评审过程：Received 5 March 2019, Revised 27 September 2019, Accepted 19 November 2019, Available online 22 November 2019, Version of Record 28 November 2019.

论文官网地址：https://doi.org/10.1016/j.patcog.2019.107118