Information Fusion in Biometrics
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
Dynamic bayesian networks: representation, inference and learning
Dynamic bayesian networks: representation, inference and learning
Multimodal Biometric Authentication Using Quality Signals in Mobile Communications
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
Robust features for frontal face authentication in difficult image conditions
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
The BANCA database and evaluation protocol
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
A comparison of photometric normalisation algorithms for face verification
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Improving fusion with margin-derived confidence in biometric authentication tasks
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
An overview of text-independent speaker recognition: From features to supervectors
Speech Communication
Measuring sample distortions in face recognition
Proceedings of the 2nd ACM workshop on Multimedia in forensics, security and intelligence
Measuring measures for face sample quality
MiFor '11 Proceedings of the 3rd international ACM workshop on Multimedia in forensics and intelligence
Speaker verification in score-ageing-quality classification space
Computer Speech and Language
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We present a methodology of reliability estimation in the multimodal biometric verification scenario. Reliability estimation has shown to be an efficient and accurate way of predicting and correcting erroneous classification decisions in both unimodal (speech, face, online signature) and multimodal (speech and face) systems. While the initial research results indicate the high potential of the proposed methodology, the performance of the reliability estimation in a multimodal setting has not been sufficiently studied or evaluated. In this paper, we demonstrate the advantages of using the unimodal reliability information in order to perform an efficient biometric fusion of two modalities. We further show the presented method to be superior to state-of-the-art multimodal decision-level fusion schemes. The experimental evaluation presented in this paper is based on the popular benchmarking bimodal BANCA database.