Proceedings of the 2023 International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2023)

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Studies Advanced in Robust Face Recognition under Complex Light Intensity

Authors
Zedong Fang1, *, Zhuoli Zhou2
1Alibaba Cloud Big Data Application College, Zhuhai College of Science and Technology, zhuhai, China, 519040
2School of computing, Zhuhai College of Science and Technology, zhuhai, China, 519040
*Corresponding author. Email: zedongfang0829@stu.zcst.edu.cn
Corresponding Author
Zedong Fang
Available Online 27 November 2023.
DOI
10.2991/978-94-6463-300-9_101How to use a DOI?
Keywords
Face recognition; light intensity; deep learning
Abstract

Facial recognition tasks aim to automatically detect, recognize, and verify facial features through computer vision and pattern recognition technology. They have been widely used in various tasks, such as security monitoring and identity authentication. Thanks to the rapid development of machine learning and deep learning technology, breakthroughs have been made in the accuracy and speed of facial recognition. However, in complex scenes, especially when lighting conditions change, accurate facial recognition remains an unresolved issue. Focusing on the above issues, this article provides a detailed introduction to the latest research progress of facial recognition algorithms in dealing with complex lighting. Specifically, we introduced the representative work from three aspects: improving the algorithm to extract more features, selecting more appropriate data sets and more dimensional data. Secondly, we quantitatively compared the changes in facial recognition accuracy under different lighting conditions. Finally, we summarized the remaining issues in the field and discussed future development directions.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2023)
Series
Advances in Computer Science Research
Publication Date
27 November 2023
ISBN
10.2991/978-94-6463-300-9_101
ISSN
2352-538X
DOI
10.2991/978-94-6463-300-9_101How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Zedong Fang
AU  - Zhuoli Zhou
PY  - 2023
DA  - 2023/11/27
TI  - Studies Advanced in Robust Face Recognition under Complex Light Intensity
BT  - Proceedings of the 2023 International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2023)
PB  - Atlantis Press
SP  - 1005
EP  - 1012
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-300-9_101
DO  - 10.2991/978-94-6463-300-9_101
ID  - Fang2023
ER  -