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Face liveness detection by exploring multiple scenic clues

机译:通过探索多种景区线索,对情愿检测

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Liveness detection is an indispensable guarantee for reliable face recognition, which has recently received enormous attention. In this paper we propose three scenic clues, which are non-rigid motion, face-background consistency and imaging banding effect, to conduct accurate and efficient face liveness detection. Non-rigid motion clue indicates the facial motions that a genuine face can exhibit such as blinking, and a low rank matrix decomposition based image alignment approach is designed to extract this non-rigid motion. Face-background consistency clue believes that the motion of face and background has high consistency for fake facial photos while low consistency for genuine faces, and this consistency can serve as an efficient liveness clue which is explored by GMM based motion detection method. Image banding effect reflects the imaging quality defects introduced in the fake face reproduction, which can be detected by wavelet decomposition. By fusing these three clues, we thoroughly explore sufficient clues for liveness detection. The proposed face liveness detection method achieves 100% accuracy on Idiap print-attack database and the best performance on self-collected face anti-spoofing database.
机译:活力检测是可靠的人脸识别的不可或缺的保证,最近受到了巨大的关注。在本文中,我们提出了三个景区线索,这些线索是非刚性运动,面部背景一致性和成像带效应,进行准确和有效的面部活力检测。非刚性运动线索表示真正面部可以表现出闪烁的面部运动,并且设计用于基于低秩矩阵分解的图像对准方法以提取这种非刚性运动。面部背景一致性线索认为,面部和背景的运动对假面部照片的一致性高,而真正的面孔的低一致性,这种一致性可以作为基于GMM的运动检测方法探索的有效活跃线。图像带效应反映了假面再现中引入的成像质量缺陷,其可以通过小波分解来检测。通过融合这三个线索,我们彻底探讨了充满活力检测的充分线索。所提出的面部活力检测方法在IDIAP打印攻击数据库上实现100%的精度,以及自收集面部防欺骗数据库上的最佳性能。

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