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. |
| Keywords: | |
| Projects |
Idiap SNSF-LOBI BBfor2 BEAT |
| Authors | |
| Added by: | [UNK] |
| Total mark: | 0 |
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