IEEE Transactions on Pattern Analysis and Machine Intelligence
Information fusion in biometrics
Pattern Recognition Letters - Special issue: Audio- and video-based biometric person authentication (AVBPA 2001)
Continuous Verification Using Multimodal Biometrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fusion in Multibiometric Identification Systems: What about the Missing Data?
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
A simple score normalisation technique for multimodal biometric authentication
International Journal of Biometrics
Multimodal biometrics: state of the art in fusion techniques
International Journal of Biometrics
An efficient technique for indexing multimodal biometric databases
International Journal of Biometrics
A method towards biometric feature fusion
International Journal of Biometrics
Outliers in biometrical data: What's old, What's new
International Journal of Biometrics
An effective multi-biometrics solution for embedded device
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Combining face and iris biometrics for identity verification
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
IEEE Transactions on Multimedia
Computers in Biology and Medicine
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Conventional multimodal biometrics systems usually do not account for missing modalities that is commonly encountered in real applications. In such cases, robust multimodal biometric verification is needed. In this paper, we present the criteria, fusion method and performance metrics of a robust multimodal biometrics verification system that verifies the client's identity at any condition of data missing. A novel adaptive Support Vector Machine (SVM) classification method is proposed for missing dimensional values. We argue that the usual performance metrics of false accept and false reject rates are insufficient yardsticks for robust verification and propose new metrics against which we benchmark our system.