Bi-modal authentication in mobile environments using session variability modelling

We present a state-of-the-art bi-modal authentication system for mobile environments, using session variability modelling. We examine inter-session variability modelling (ISV) and joint factor analysis (JFA) for both face and speaker authentication and evaluate our system on the largest bi-modal mob...

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Bibliographic Details
Main Authors: Motlicek, P., Shafey, L. E., Wallace, R., McCool, C., Marcel, S.
Format: Conference Proceeding
Language:English
Subjects:
Adaptation models
Authentication
Face
Mobile communication
Mobile handsets
Speech
Online Access:Request full text
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Summary:We present a state-of-the-art bi-modal authentication system for mobile environments, using session variability modelling. We examine inter-session variability modelling (ISV) and joint factor analysis (JFA) for both face and speaker authentication and evaluate our system on the largest bi-modal mobile authentication database available, the MOBIO database, with over 61 hours of audio-visual data captured by 150 people in uncontrolled environments on a mobile phone. Our system achieves 2.6% and 9.7% half total error rate for male and female trials respectively - relative improvements of 78% and 27% compared to previous results.
ISSN:1051-4651
2831-7475