Plenoptic Face Presentation Attack Detection.
Plenoptic Face Presentation Attack Detection.
复制标题
全光面部呈现攻击检测。
DOI：
10.1109/access.2020.2980755
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Gao,Liang
中科院分区：
文献类型：
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作者：
Zhu,Shuaishuai;Lv,Xiaobo;Feng,Xiaohua;Lin,Jie;Jin,Peng;Gao,Liang
当前人脸识别系统对呈现攻击的脆弱性极大地限制了它们在生物特征识别中的应用。在这里，我们提出了一种基于完整全光成像系统的被动呈现攻击检测方法，该系统可以使用单个探测器来获得光线的完整全光函数。此外，我们还构建了一个包含50个主题和7种不同类型呈现攻击的多维人脸数据库。我们通过实验证明，我们的方法在所有类型的表示攻击上都优于最先进的方法。
The vulnerability of current face recognition systems to presentation attacks significantly limits their application in biometrics. Herein, we present a passive presentation attack detection method based on a complete plenoptic imaging system which can derive the complete plenoptic function of light rays using a single detector. Moreover, we constructed a multi-dimensional face database with 50 subjects and seven different types of presentation attacks. We experimentally demonstrated that our approach outperforms the state-of-the-art methods on all types of presentation attacks.