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Missing Data Estimation in Multi-biometric Identification and Verification

Damer, Naser and Führer, Jan Benedikt and Kuijper, Arjan :
Missing Data Estimation in Multi-biometric Identification and Verification.
In: 2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications. IEEE, Inc., New York
[Conference or Workshop Item] , (2013)

Abstract

In the practical use of multi-biometric solutions, biometric sources involved in producing the verification or identification decision do occasionally fail to produce results. This work discusses solutions for missing data in multi-biometric score-level fusion. A missing data estimation solution based on support vector regression was presented in this work and compared to four baseline solutions. The evaluation was carried under both the verification and the identification scenarios in an effort to show the effect of missing data estimation on the relatively understudied multi-biometric identification scenario. Evaluation was performed on the Biosecure DS2 score database and satisfying performance was achieved under both biometric scenarios.

Item Type: Conference or Workshop Item
Erschienen: 2013
Creators: Damer, Naser and Führer, Jan Benedikt and Kuijper, Arjan
Title: Missing Data Estimation in Multi-biometric Identification and Verification
Language: English
Abstract:

In the practical use of multi-biometric solutions, biometric sources involved in producing the verification or identification decision do occasionally fail to produce results. This work discusses solutions for missing data in multi-biometric score-level fusion. A missing data estimation solution based on support vector regression was presented in this work and compared to four baseline solutions. The evaluation was carried under both the verification and the identification scenarios in an effort to show the effect of missing data estimation on the relatively understudied multi-biometric identification scenario. Evaluation was performed on the Biosecure DS2 score database and satisfying performance was achieved under both biometric scenarios.

Publisher: IEEE, Inc., New York
Uncontrolled Keywords: Business Field: Digital society, Biometric fusion, Biometric identification systems, Multibiometrics, Data imputation
Divisions: Department of Computer Science
Department of Computer Science > Interactive Graphics Systems
Event Title: 2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications
Date Deposited: 12 Nov 2018 11:16
DOI: 10.1109/BIOMS.2013.6656147
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