Biometric person authentication with liveness detection based on audio-visual fusion

In this paper, we propose two new approaches for extracting mouth features for authenticating the person identity with liveness checks. The novel correlated audio-lip features and tensor lip-motion features allow liveness checks to be included in the person identity authentication systems, and ensures that the biometric cues are acquired from a live person who is actually present at the time of capture. Incorporating liveness check functionality in identity authentication systems can guard the system against the advanced spoofing attempts such as manufactured or replayed videos.