Difference between revisions of "Publications:Combining Biometric Evidence for Person Authentication"
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{{PublicationSetupTemplate|Author=Josef Bigun, J. Fierrez-Aguilar, J. Ortega-Garcia, J. Gonzalez-Rodriguez | {{PublicationSetupTemplate|Author=Josef Bigun, J. Fierrez-Aguilar, J. Ortega-Garcia, J. Gonzalez-Rodriguez | ||
|PID=408397 | |PID=408397 | ||
| − | |Name=Bigun, Josef | + | |Name=Bigun, Josef (josef) (Högskolan i Halmstad (2804), Akademin för informationsteknologi (16904), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), Intelligenta system (IS-lab) (3941));Fierrez-Aguilar, J. (Universidad Politecnica de Madrid, Spain);Ortega-Garcia, J. (Universidad Politecnica de Madrid, Spain);Gonzalez-Rodriguez, J. (Universidad Politecnica de Madrid, Spain) |
|Title=Combining Biometric Evidence for Person Authentication | |Title=Combining Biometric Evidence for Person Authentication | ||
|PublicationType=Conference Paper | |PublicationType=Conference Paper | ||
Latest revision as of 21:38, 30 September 2016
| Title | Combining Biometric Evidence for Person Authentication |
|---|---|
| Author | Josef Bigun and J. Fierrez-Aguilar and J. Ortega-Garcia and J. Gonzalez-Rodriguez |
| Year | 2005 |
| PublicationType | Conference Paper |
| Journal | |
| HostPublication | Advanced Studies in Biometrics : Summer School on Biometrics, Alghero, Italy, June 2-6, 2003 |
| Conference | Summer School on Biometrics, Alghero, Italy, June 2-6, 2003. |
| DOI | http://dx.doi.org/10.1007/11493648_1 |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:408397 |
| Abstract | Humans are excellent experts in person recognition and yet they do not perform excessively well in recognizing others only based on one modality such as single facial image. Experimental evidence of this fact is reported concluding that even human authentication relies on multimodal signal analysis. The elements of automatic multimodal authentication along with system models are then presented. These include the machine experts as well as machine supervisors. In particular, fingerprint and speech based systems will serve as illustration. A signal adaptive supervisor based on the input biometric signal quality is evaluated. |
