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Joint Reflectance Field Estimation and Sparse Representation for Face Image Illumination Preprocessing and Recognition

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Abstract

Illumination preprocessing is an important ingredient for handling lighting variation face recognition challenge. Nonetheless, existing methods are usually designed to be independent of the face recognition methods and the interaction between them is not yet well explored. In this paper, we formulate the face image illumination preprocessing and recognition into a unified sparse representation framework and propose a novel joint reflectance field estimation and sparse representation (JRSR) method for face recognition under extreme lighting conditions. The proposed method separates the identify factor and the interfered illumination of a query sample simultaneously by one nonconvex sparse optimizing model. We also present an efficient approximation algorithm to solve JRSR in this paper. Evaluation on several face databases and the experimental results of face recognition with illumination variation clearly demonstrate the advantages of our proposed JRSR algorithm in illumination preprocessing efficiency and recognition accuracy.

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Acknowledgements

The authors would like to thank the editor and the anonymous reviewers for their critical and constructive comments and suggestions. This work was supported by the The National Natural Science Foundation of China under Grant 61873106, National Nature Science Foundation of Jiangsu Province under Grant BK20171264, Jiangsu Qing Lan Project to Cultivate Middle-aged and Young Science Leaders, Jiangsu Six Talent Peak Project under Grants XYDXX-047, XYDXX-140, University Science Research General Research General Project of Jiangsu Province under Grant 18KJB520005, 19KJB520004, the Innovation Fund Project for Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education under Grant JYB201609, Lianyungang Hai Yan Plan under Grants 2018-ZD003, 2018 -QD-001, 2018-QD-012,the Science and Technology Project of Lianyungang High-tech Zone Under Grants ZD201910, ZD201912 and Natural Science Foundation Project of Huaihai Institute of Technology under Grant Z2017005.

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Author notes

  1. Jian Zhang and Weihua Liu are co-first authors.

Authors and Affiliations

  1. Department of Computer Engineering, Jiangsu Ocean University, Lianyungang, 222000, People’s Republic of China

    Jian Zhang, Liling Bo, Heng Zhang, Hongran Li & Shuai Xu

  2. Jining University, Jining, 273100, People’s Republic of China

    Weihua Liu

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  1. Jian Zhang
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  3. Liling Bo
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  4. Heng Zhang
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Correspondence to Jian Zhang.

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Zhang, J., Liu, W., Bo, L. et al. Joint Reflectance Field Estimation and Sparse Representation for Face Image Illumination Preprocessing and Recognition. Neural Process Lett 54, 3551–3564 (2022). https://doi.org/10.1007/s11063-020-10316-6

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