Occluded Face Recognition Based on the Deep Learning

被引:0
|
作者
Wu, Gui [1 ]
Tao, Jun [2 ,3 ]
Xu, Xun [4 ]
机构
[1] Jianghan Univ, Educ Adm Off, Wuhan 430056, Peoples R China
[2] Jianghan Univ, Sch Math & Comp Sci, Wuhan 430056, Peoples R China
[3] Rowan Univ, Dept Elect & Comp Engn, Glassboro, NJ 08028 USA
[4] Jianghan Univ, Grad Sch, Wuhan 430056, Peoples R China
关键词
Deep Learning; Face Recognition; Convolutional Neural Network; Triplet Loss Function; SEARCH;
D O I
10.1109/ccdc.2019.8832330
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the aggravation of social public security problems, the face recognition without occluded parts can no longer meet the needs of modern society. All kinds of face recognitions in complex environment need to be realized in the real situations. The paper proposed a new method to recognize the occluded face based on the deep learning. The face recognition model is trained and learned based on convolution neural network of the deep learning, which has strong robustness to illumination difference, facial expression change and facial occlusion. Through a large number of experimental tests and result analysis, the occluded face recognition rate can reach up to 98.6%. Therefore, this method proposed in the paper realizes face recognition with occlusion in complex environment and meets the needs of practical applications.
引用
收藏
页码:793 / 797
页数:5
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