Face liveness detection with recaptured feature extraction

机译：具有重新捕获的特征提取的面部活动度检测

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摘要

Face recognition systems can be tricked by photos or videos with virtual faces. It is crucial for a safe face recognition system to distinguish genuine user's faces (i.e., the first captured images of real scene) and spoof faces (i.e., recaptured images of photographs or videos). Existing face liveness methods often use single image feature to address face spoofing problems, which are not reliable and robust. In this paper, we analyze the differences between genuine face images and spoof images, and propose to extract three types of features, i.e., specular reflection ratio, Hue channel distribution and blurriness, to determine whether a face image is captured from genuine face or not. Experimental results on NUAA photograph imposter database show the competitive performance of our method comparing with several state-of-the-art methods.

机译：人脸识别系统可能会被带有虚拟人脸的照片或视频所欺骗。对于安全的面部识别系统来说，区分真实用户的面部（即真实场景的第一张捕获图像）和欺骗性面部（即照片或视频的重新捕获图像）至关重要。现有的面部活跃度方法通常使用单个图像特征来解决面部欺骗问题，这是不可靠且不可靠的。在本文中，我们分析了真实面部图像和欺骗图像之间的差异，并提出了提取三种类型的特征，即镜面反射率，色相通道分布和模糊度，以确定是否从真实面部中捕获面部图像。。 NUAA照片冒名者数据库上的实验结果表明，与几种最新方法相比，我们的方法具有竞争优势。

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来源
《2017 International Conference on Security, Pattern Analysis, and Cybernetics》|2017年|429-432|共4页
会议地点 Shenzhen(CN)
作者
Xiao Luan; Huaming Wang; Weihua Ou; Linghui Liu;
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作者单位

College of Computer, Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China;

College of Computer, Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China;

School of Big Data and Computer Science, Guizhou Normal, University Guiyang, China;

College of Software Engineering, Chongqing University of Posts and Telecommunications Chongqing, China;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Face; Reflection; Feature extraction; Image color analysis; Support vector machines; Lighting; Face recognition;

机译：人脸;反射;特征提取;图像色彩分析;支持向量机;照明;人脸识别;;

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Face liveness detection with recaptured feature extraction

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