三维人脸成像及重建技术综述  

3D face imaging and reconstruction technology:a review

作　　者：刘菲[1] 张堃博 杨青[1] 周树波 王云龙 孙哲南[2] Liu Fei;Zhang Kunbo;Yang Qing;Zhou Shubo;Wang Yunlong;Sun Zhenan(School of Management and Engineering,Capital University of Economics and Business,Beijing 100070,China;National Laboratory of Pattern Recognition(NLPR),Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China;College of Information Science and Technology,Donghua University,Shanghai 201620,China)

机构地区：[1]首都经济贸易大学管理工程学院,北京100070 [2]中国科学院自动化研究所模式识别实验室,北京100190 [3]东华大学信息科学与技术学院,上海201620

出　　处：《中国图象图形学报》2024年第9期2441-2470,共30页Journal of Image and Graphics

基　　金：国家自然科学基金项目(61806197,61803372,62071468,U23B2054,62276263)。

摘　　要：得益于新型三维视觉测量技术及深度学习模型的飞速发展,三维视觉成为人工智能、虚拟现实等领域的重要支撑技术,三维人脸成像及重建技术取得了突破性进展,不仅能够更好地应对光照、遮挡、表情和姿态等变化,同时增大了伪造攻击难度,大大推动了真实感“虚拟数字人”的重建与渲染,有效提升了人脸系统的安全性。本文对三维人脸成像技术和重建模型进行了全面综述,尤其对基于深度学习的三维人脸重建进行系统深入地分析。首先,对三维人脸成像设备及采集系统进行详细梳理及对比归纳,并介绍了基于新传感技术的人脸成像系统;然后,对基于深度学习的三维人脸重建模型进行系统分析,从输入数据源角度分为基于单目图像、基于多目图像、基于视频和基于语音的三维人脸重建算法4类。通过深入分析,总结三维人脸成像的研究现状及面临的难点与挑战,对未来发展方向及应用进行积极探讨与展望。本文涵盖了近5年经典的三维人脸成像及重建相关的技术与研究,为人脸研究、发展和应用提供了很好的参考。As the breakthrough technology of artificial intelligence(AI)in the big data era,deep learning(DL)has prompted the renewed upsurge of face technology.Powered by rapid developments of new technologies,such as threedimensional(3D)vision measurement,image processing chips,and DL models,3D vision transformed into a key support⁃ing technology in AI,visual reality,etc.The studies and applications of 3D facial imaging and reconstruction technologies have achieved important breakthroughs.3D face data represent exact multidimensional facial attributes on account of rich visual information,such as texture,shape,space,etc.Moreover,3D face data shows robust changes in large occlusions,expressions,and poses and increases the difficulty of forgery attack.Therefore,3D face imaging and reconstruction effec⁃tively promote realistic“virtual digital human”reconstruction and rendering.In addition,these processes contribute to the improved security of the face system.In this paper,we comprehensively study the 3D face imaging technology and recon⁃struction models.The 3D face reconstruction methods based on DL are systematically and deeply analyzed.First,the development and innovation of 3D face imaging devices and capturing systems are discussed through a summary of public 3D face datasets.The devices and systems include consumer imaging devices(such as Kinect)and complex hybrid sys⁃tems that fuse active and passive 3D imaging technologies to achieve precise geometry and appearance.Moreover,3D face imaging based on new sensing technologies are introduced.Then,from the perspective of input resources,3D face recon⁃struction methods based on DL are categorized into monocular,multiview,video and audio reconstruction methods.3D face imaging technology introduces public classic 3D face datasets,popular 3D face imaging devices,and capturing sys⁃tems.Most high-quality 3D face datasets,such as BU-3DFE,FaceScape and FaceVerse,are captured through a large imaging volume with a certain number of high-resolution cameras and control

关 键 词：三维人脸成像 三维人脸重建 深度学习(DL) 生成对抗网络(GAN) 隐式神经表示(INR) 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]