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28 March 2023 Research advanced in occluded face recognition
Zhenyu Fang, Yuruo Lei, Gang Yuan
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Proceedings Volume 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022); 125662G (2023) https://doi.org/10.1117/12.2667912
Event: Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 2022, Chongqing, China
Abstract
The domain of computer vision's most popular study area has always been face recognition which aims to identify different face images and predict the corresponding identity information through feature analysis and modeling. In practical applications, a number of variables, including lighting, posture, and clarity, have an impact on facial recognition accuracy. Among them, the most challenging scene is occlusion face recognition, which will cause feature loss, local coherence and alignment errors to greatly inhibit the accuracy and generalization ability of the face model. Based on detailed literature research and analysis, this paper provides a comprehensive evaluation of the research progress of occluded face recognition. Specifically, based on the introduction of classical face recognition technology, we further discuss the design ideas, basic framework, advantages and disadvantages of representative occlusion face recognition methods from two aspects: robust feature extraction and robust classifier. Finally, we summarize the main challenges and give an outlook on the future research development of object detection.
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Zhenyu Fang, Yuruo Lei, and Gang Yuan "Research advanced in occluded face recognition", Proc. SPIE 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 125662G (28 March 2023); https://doi.org/10.1117/12.2667912
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KEYWORDS
Facial recognition systems
Feature extraction
Detection and tracking algorithms
Principal component analysis
Education and training
Technology
Deep learning
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