Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 5
1535-1541

Improved face feature rectification network for occluded face recognition

Chen Qiuyu
Lu Tianliang
College of Information & Cyber Security, People's Public Security University of China, Beijing 100038, China
DOI: 10.19734/j.issn.1001-3695.2022.08.0447

Abstract

The accuracy of existing face recognition models cannot improve due to the influence of masks and other occlusion factors. The current mainstream research methods integrate and apply the occluded and unoccluded scenes to multiple scenes after separate training. Aiming at the limitation of occluded face recognition model, this paper proposed an improved face feature rectification network(FFR-Net) model. This model could be used for face recognition with or without occlusion, and be applied to mask and glasses occlusion recognition scenes. FFR-Net proposed a face feature rectification module. In order to make full use of the feature information of the unocclusion area, the spatial branch of the module introduced involution operator to expand the image information interaction area and enhance the face feature information in the spatial range. The channel branch introduced coordinate attention to capture cross channel information to enhance the feature representation, which was conducive for the model to locate and identify the target area more accurately. Using Meta-ACON as a new dynamic activation function, it improved model generalization and calculation accuracy by dynamically adjusting the degree of linearity or nonlinearity. Finally, this paper trained the improved FFR-Net on the CASIA-Webface processed face dataset with or without mask occlusion. The accuracy of the test results on the LFW processed face dataset with or without mask occlusion and Meglass dataset are 82.50% and 89.75% respectively, which is superior to the existing algorithm, and verifies the effectiveness of the proposed method.

Foundation Support

中国人民公安大学2022年基本科研业务费项目
国家社科基金重大项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.08.0447
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 5
Section: Technology of Graphic & Image
Pages: 1535-1541
Serial Number: 1001-3695(2023)05-039-1535-07

Publish History

[2022-12-07] Accepted Paper
[2023-05-05] Printed Article

Cite This Article

陈秋雨, 芦天亮. 改进人脸特征矫正网络的遮挡人脸识别方法 [J]. 计算机应用研究, 2023, 40 (5): 1535-1541. (Chen Qiuyu, Lu Tianliang. Improved face feature rectification network for occluded face recognition [J]. Application Research of Computers, 2023, 40 (5): 1535-1541. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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