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 [BibTeX] [Marc21]
Bi-Modal Biometric Authentication on Mobile Phones in Challenging Conditions
Type of publication: Journal paper
Citation: Khoury_IMAVIS_2014
Publication status: Published
Journal: Image and Vision Computing
Year: 2014
Pages: 1147-1160
Crossref: Khoury_Idiap-RR-30-2013:
URL: http://www.sciencedirect.com/s...
DOI: http://dx.doi.org/10.1016/j.imavis.2013.10.001
Abstract: This paper examines the issue of face, speaker and bi-modal authentication in mobile environments when there is significant condition mismatch. We introduce this mismatch by enrolling client models on high quality biometric samples obtained on a laptop computer and authenticating them on lower quality biometric samples acquired with a mobile phone. To perform these experiments we develop three novel authentication protocols for the large publicly available MOBIO database. We evaluate state-of-the-art face, speaker and bi-modal authentication techniques and show that inter-session variability modelling using Gaussian mixture models provides a consistently robust system for face, speaker and bi-modal authentication. It is also shown that multi-algorithm fusion provides a consistent performance improvement for face, speaker and bi-modal authentication. Using this bi-modal multi-algorithm system we derive a state-of-the-art authentication system that obtains a half total error rate of 6.3% and 1.9% for Female and Male trials, respectively.
Projects Idiap
Authors Khoury, Elie
El Shafey, Laurent
McCool, Chris
Günther, Manuel
Marcel, Sébastien
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