Title :
Face liveness detection by exploring multiple scenic clues
Author :
Junjie Yan ; Zhiwei Zhang ; Zhen Lei ; Dong Yi ; Li, Stan Z.
Author_Institution :
Nat. Lab. of Pattern Recognition, Inst. of Autom., Beijing, China
Abstract :
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.
Keywords :
Gaussian processes; face recognition; feature extraction; image motion analysis; matrix decomposition; visual databases; wavelet transforms; GMM-based motion detection method; Idiap print-attack database; face antispoofing database; face liveness detection method; face recognition; face-background consistency; facial motions; fake face reproduction; fake facial photo consistency; genuine face; image alignment approach; imaging banding effect; imaging quality defects; low rank matrix decomposition; nonrigid motion extraction; scenic clues; wavelet decomposition; Databases; Entropy; Face; Feature extraction; Market research; Mouth; Noise;
Conference_Titel :
Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4673-1871-6
Electronic_ISBN :
978-1-4673-1870-9
DOI :
10.1109/ICARCV.2012.6485156