计算机应用研究2024，Vol.41Issue(1)：277-281,287,6.DOI:10.19734/j.issn.1001-3695.2023.06.0266
基于对比学习的多特征融合戴口罩人脸识别
Multi feature fusion for masked face recognition based on contrastive learning
陈岸明 1林群雄 2刘伟强1
作者信息
- 1. 清华大学深圳国际研究生院,广东深圳 518055
- 2. 广东省公安科技协同创新中心,广州 510050
- 折叠
摘要
Abstract
With the development of computer vision technology and the popularization of intelligent terminals,facial recogni-tion under mask occlusion has become an important part of character identity information recognition.The large area occlusion of masks poses great challenges to the learning of facial features.To solve this problem,this paper proposed a multi feature fu-sion based masked face recognition algorithm based on contrastive learning.This algorithm improved the traditional face feature vector learning loss function based on the triple relationship.It proposed a loss function based on the multi-instance relation-ship,which fully excavated the intra-modal and inter-modal correlation between multiple positive and negative samples of the masked face and the full face.Then,the features with high discrimination ability were learnt from the face.Meanwhile,it combined the local features such as eyebrows and eyes,as well as global features such as contours,to learn the effective fea-ture vector representation of the masked face.This paper compared it with the benchmark algorithm on real masked face data-sets and generated masked face data.The experimental results show that the proposed algorithm has higher recognition accura-cy than the traditional triple loss function and feature fusion model.关键词
戴口罩人脸识别/对比学习/特征融合/口罩生成Key words
masked face recognition/contrastive learning/feature fusion/mask generation分类
信息技术与安全科学引用本文复制引用
陈岸明,林群雄,刘伟强..基于对比学习的多特征融合戴口罩人脸识别[J].计算机应用研究,2024,41(1):277-281,287,6.
