电子科技大学学报2024，Vol.53Issue(2)：252-258,7.DOI:10.12178/1001-0548.2023012
基于关键特征增强机制的3D人脸识别
3D Face Recognition Based on Key Feature Enhancement Mechanism
摘要
Abstract
3D face recognition is an important part of the field of computer vision.Pointnet relies on deep learning to solve the disorder of point clouds and realize the global feature extraction.However,due to the lack of detailed texture of point clouds,it is difficult to realize face recognition in complex situations only by global features.In deal with the above problems,a local feature descriptor is proposed to describe the local spatial geometric features of the point clouds,and a key feature enhancement mechanism is introduced to enhance the key features of the face through the probability distribution,which can reduce the interference of unnecessary features and effectively improve the accuracy of the model.Experiments were carried out on public data sets CASIA-3D,Lock3DFace and Bosphorus.The results show that our method can deal well with the change of expression,partial occlusion and interference of head pose,especially in weak light conditions,compared with RP-Net,the accuracy is improved by 1.1 percent,and the method also has good real-time performance.关键词
3D人脸识别/深度学习/局部特征描述子/特征增强/点云数据Key words
3D face recognition/deep learning/local feature descriptor/feature enhancement/point cloud分类
信息技术与安全科学引用本文复制引用
王奇,钱伟中,雷航,王旭鹏..基于关键特征增强机制的3D人脸识别[J].电子科技大学学报,2024,53(2):252-258,7.基金项目
国家自然科学基金(61802052) （61802052）
喀什地区科技计划项目(KS2023029) （KS2023029）
