人脸活体检测综述

A Review on Face Anti-spoofing

人脸活体检测是为了提高人脸识别系统安全性而需要重点研究的问题.本文首先从人脸活体检测的问题出发,分个体、类内、类间三个层面对人脸活体检测存在的困难与挑战进行了阐述分析.接下来,本文以算法使用的分类线索为主线,分类别对人脸活体检测算法及其优缺点进行了梳理和总结.之后,本文就常用人脸活体检测数据集的特点、数据量、数据多样性等方面进行了对比分析,对算法评估常用的性能评价指标进行了阐述,总结分析了代表性人脸活体检测方法在照片视频类数据集CASIA-MFSD、Replay-Attack、Oulu-NPU、SiW以及面具类数据集3DMAD、SMAD、HKBU-MARsV2上的实验性能.最后本文对人脸活体检测未来可能的发展方向进行了思考和探讨.

Face anti-spoofing is an important research field for ensuring the security of face recognition system. In this paper, we first discuss the difficulties and challenges in the development of face anti-spoofing. Then we take the classification clues utilized by the methods as the main line to review the achievements in the study of face anti-spoofing.Next, we analyze the characteristics, data volume and data diversity of commonly used face anti-spoofing datasets. The evaluation metrics of performances commonly used in algorithm evaluation are expounded. We summarize and analyze the performances of representative face anti-spoofing methods on CASIA-MFSD, Replay-Attack, Oulu-NPU, SiW, 3 DMAD,SMAD and HKBU-MARsV2 datasets. Finally, we discuss the future development direction of face anti-spoofing.