Audio-Visual Multimodal Fusion for Biometric Person Authentication and Liveness Verification

摘要

In this paper we propose a multimodal fusion framework based on novel face-voice fusion techniques for biometric person authentication and liveness verification. Checking liveness guards the system against spoof/replay attacks by ensuring that the biometric data is captured from an authorised live person. The proposed framework based on bi-modal feature fusion, cross-modal fusion as well as 3D shape and texture fusion techniques, allow a significant improvement in system performance against impostor attacks, type-1 replay attacks (still photo and pre-recorded audio), and challenging type-2 replay attacks(CG animated video from a still photo and pre-recorded audio) and robustness to pose and illumination variations.