Face illumination recovery for the deep learning feature under severe illumination variations

作者：

Highlights：

• The illumination recovery model converts severe varying illumination to slight/moderate varying illumination for the deep learning feature.

• The gradient descent algorithm is employed to tackle the illumination recovery model.

• The GRI is generated by normalizing singular values of the logarithm version of the severe illumination variation face image to have unit L2-norm.

• The GRIR preserves better face inherent information than the GRI.

摘要

•The illumination recovery model converts severe varying illumination to slight/moderate varying illumination for the deep learning feature.•The gradient descent algorithm is employed to tackle the illumination recovery model.•The GRI is generated by normalizing singular values of the logarithm version of the severe illumination variation face image to have unit L2-norm.•The GRIR preserves better face inherent information than the GRI.

论文关键词：Severe illumination variations,Face recognition,Illumination recovery model,Deep learning feature

论文评审过程：Received 2 December 2019, Revised 9 September 2020, Accepted 23 October 2020, Available online 24 October 2020, Version of Record 1 November 2020.

论文官网地址：https://doi.org/10.1016/j.patcog.2020.107724