Bi-Modal Biometric Authentication on Mobile Phones in Challenging Conditions

• Published in: Image and Vision Computing, p. 0-0
• Publication date: 2013

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.

Reference

• EPFL-ARTICLE-192474
• Related documents: http://publications.idiap.ch/index.php/publications/showcite/Khoury_Idiap-RR-30-2013

Record created on 2013-12-19, modified on 2017-05-10