南京理工大学学报（自然科学版）2026，Vol.50Issue(2)：152-160,9.DOI:10.14177/j.cnki.32-1397n.2026.50.02.005
基于双通道FaceNet的遮挡人脸识别
Occluded face recognition based on dual-channel FaceNet
摘要
Abstract
In the case of large area face occlusion,the available image feature information of traditional FaceNet is greatly reduced.To address this problem,occluded face recognition method based on dual-channel FaceNet is proposed.This paper innovatively constructs a dual-channel FaceNet network model,which includes global channel and local feature channel.This method can enhance the network's learning of local features,improve the utilization of available features,and improve the recognition accuracy of FaceNet in the case of occlusion.In the case of no occlusion,the dual-channel FaceNet improves the recognition accuracy by 0.47%compared with the traditional FaceNet,while in the case of occlusion,the recognition accuracy is improved by 5.10%.In the scenario of simulating mutual occlusion of faces,when the occlusion ratio is 40%and 60%,the recognition accuracy of dual-channel FaceNet is improved by 3.99%and 9.09%,respectively.Experimental results demonstrate that the effectiveness of dual-channel FaceNet for occluded face recognition.关键词
遮挡人脸/FaceNet网络/双通道/局部特征/欧氏距离Key words
occluded face/FaceNet network/dual-channel/local feature/Euclidean distance分类
信息技术与安全科学引用本文复制引用
任星光,丁晨寅,段纳,孙浩..基于双通道FaceNet的遮挡人脸识别[J].南京理工大学学报（自然科学版）,2026,50(2):152-160,9.基金项目
国家自然科学基金(62173166) （62173166）
