A New Face Recognition Method for Intelligent Security
With the advent of the era of artificial intelligence and big data, intelligent security robots not only improve the efficiency of the traditional intelligent security industry but also propose higher requirements for intelligent security. Aiming to solve the problem of long recognition time and hig...
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doaj-a73bb60d3b45475292d405fdd6ad00f42020-11-25T02:19:45ZengMDPI AGApplied Sciences2076-34172020-01-0110385210.3390/app10030852app10030852A New Face Recognition Method for Intelligent SecurityZhenzhou Wang0Xu Zhang1Pingping Yu2Wenjie Duan3Dongjie Zhu4Ning Cao5School of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, ChinaSchool of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, ChinaSchool of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, ChinaSchool of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, ChinaSchool of Computer Science and Technology, Harbin Institute of Technology, Weihai 264209, ChinaSchool of Internet of Things and Software Technology, Wuxi Vocational College of Science and Technology, Wuxi 214028, ChinaWith the advent of the era of artificial intelligence and big data, intelligent security robots not only improve the efficiency of the traditional intelligent security industry but also propose higher requirements for intelligent security. Aiming to solve the problem of long recognition time and high equipment cost of intelligent security robots, we propose a new face recognition method for intelligent security in this paper. We use the Goldstein branching method for phase unwrapping, which can improve the three-dimensional (3D) face reconstruction effect. Subsequently, by using the three-dimensional face recognition method based on face radial curve elastic matching, different weights are assigned to different curve recognition similarity for weighted fusion as the total similarity for recognition. Experiments show that the method has a higher face recognition rate and is robust to attitude, illumination, and noise.https://www.mdpi.com/2076-3417/10/3/852intelligent securitygrating projection3d reconstructionphase unwrapping3d face recognitionlayered elastic matchingattitude robustness |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhenzhou Wang Xu Zhang Pingping Yu Wenjie Duan Dongjie Zhu Ning Cao |
spellingShingle |
Zhenzhou Wang Xu Zhang Pingping Yu Wenjie Duan Dongjie Zhu Ning Cao A New Face Recognition Method for Intelligent Security Applied Sciences intelligent security grating projection 3d reconstruction phase unwrapping 3d face recognition layered elastic matching attitude robustness |
author_facet |
Zhenzhou Wang Xu Zhang Pingping Yu Wenjie Duan Dongjie Zhu Ning Cao |
author_sort |
Zhenzhou Wang |
title |
A New Face Recognition Method for Intelligent Security |
title_short |
A New Face Recognition Method for Intelligent Security |
title_full |
A New Face Recognition Method for Intelligent Security |
title_fullStr |
A New Face Recognition Method for Intelligent Security |
title_full_unstemmed |
A New Face Recognition Method for Intelligent Security |
title_sort |
new face recognition method for intelligent security |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2020-01-01 |
description |
With the advent of the era of artificial intelligence and big data, intelligent security robots not only improve the efficiency of the traditional intelligent security industry but also propose higher requirements for intelligent security. Aiming to solve the problem of long recognition time and high equipment cost of intelligent security robots, we propose a new face recognition method for intelligent security in this paper. We use the Goldstein branching method for phase unwrapping, which can improve the three-dimensional (3D) face reconstruction effect. Subsequently, by using the three-dimensional face recognition method based on face radial curve elastic matching, different weights are assigned to different curve recognition similarity for weighted fusion as the total similarity for recognition. Experiments show that the method has a higher face recognition rate and is robust to attitude, illumination, and noise. |
topic |
intelligent security grating projection 3d reconstruction phase unwrapping 3d face recognition layered elastic matching attitude robustness |
url |
https://www.mdpi.com/2076-3417/10/3/852 |
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