基于双摄像头下的活体人脸检测方法  

Live Face Detection Method Based on Dual Camera

作　　者：张鹤 孙瑜[1] ZHANG He;SUN Yu(School of information,Yunnan Normal University,Kunming 650000,China)

机构地区：[1]云南师范大学信息学院,云南昆明650000

出　　处：《软件》2020年第7期51-56,共6页Software

基　　金：国家自然科学基金资助项目(60903131);教育部科学技术研究重点资助项目(210210);云南省应用基础研究计划面上资助项目(2009ZC0052M)。

摘　　要：为了解决以往身份认证中的人脸识别问题,提出了一种基于可见光与红外摄像头获取人像差异的方式来实现活体人脸检测。首先利用近红外相机成像特性防止假脸攻击问题,然后针对近红外相机获取的图像不能利用现有的大量可见光照片进行人脸匹配问题,利用扩大近红外图像中检测到的活体人脸特征框,放到可见光图像中同坐标位置等比例"裁剪"的方式来确定活体人脸在可见光图像中的位置,最后对"裁剪"后的图像进行人脸检测,获取面积最大的人脸(即活体人脸)。在自建样本库中场景实验分析,所提出的方法能够抵御假脸攻击的同时,又能保证活体人脸检测的准确度。The paper proposed a obtaining human image difference between visible light camera and infrared camera in order to solve the problems of face recognition in the past identity authentication. First, Use of near-infrared camera imaging characteristics to prevent false face attack. Then, for the image acquired by the near-infrared camera, the existing large number of visible light photos cannot be used for face matching, and the feature frame of the living face detected in the near-infrared image is enlarged. Then, we use the Utilizing enlarged live face feature frames detected in near-infrared images. the enlarged face coordinate information was put into the color image to be "clipped" in the same proportion as the coordinate position, and the largest face(i.e. the living face) was obtained according to the "clipped" image. Finally, In the self-built sample database, the method proposed by the scene experiment analysis under different error factors can resist the false face attack and ensure the accuracy of the living face detection.

关 键 词：双摄像头 活体人脸检测 近红外 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]