Co-inertia analysis for "liveness" test in audio-visual biometrics

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Abstract
In biometrics, it is crucial to detect impostors and thwart replay attacks. However, few researches have focused yet on the "liveness" verification. This test ensures that biometric cues being acquired are actual measurements from a live person who is present at the time of capture. Here, we propose a speaker independent "liveness" verification method for audio-video identification systems. It uses the correlation that exists between the lip movements and the speech produced. Two data analysis methods are considered to model this statistical link. Finally, according to tests carried out on the XM2VTS database, the best liveness verification EER achieved is 12.5%.