Facelivenet: End-To-End Networks Combining Face Verification With Interactive Facial Expression-Based Liveness Detection
2018 24TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR)(2018)
摘要
The effectiveness of the state-of-the-art face verification/recognition algorithms and the convenience of face recognition greatly boost the face-related biometric authentication applications. However, existing face verification architectures seldom integrate any liveness detection or keep such stage isolated from face verification as if it was irrelevant. This may potentially result in the system being exposed to spoof attacks between the two stages. This work introduces FaceLiveNet, a holistic end-to-end deep networks which can perform face verification and liveness detection simultaneously. An interactive scheme for facial expression recognition is proposed to perform liveness detection, providing better generalization capacity and higher security level. The proposed framework is low-cost as it relies on commodity hardware instead of costly sensors, and lightweight with much fewer parameters comparing to the other popular deep networks such as VGG16 and FaceNet. Experimental results on the benchmarks LFW, YTF, CK+, OuluCASIA, SFEW, FER2013 demonstrate that the proposed FaceLiveNet can achieve state-of-art performance or better for both face verification and facial expression recognition. We also introduce a new protocol to evaluate the global performance for face authentication with the fusion of face verification and interactive facial expression-based liveness detection.
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关键词
face-related biometric authentication applications,FaceLiveNet,holistic end-to-end deep networks,facial expression recognition,face authentication,interactive facial expression-based liveness detection,end-to-end networks,face verification-recognition algorithms,face verification architectures
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