IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrating Faces and Fingerprints for Personal Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Person Identification Using Multiple Cues
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)
Large-Scale Evaluation of Multimodal Biometric Authentication Using State-of-the-Art Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
IR and visible light face recognition
Computer Vision and Image Understanding
Score normalization in multimodal biometric systems
Pattern Recognition
Combining face and iris biometrics for identity verification
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Classic Works of the Dempster-Shafer Theory of Belief Functions
Classic Works of the Dempster-Shafer Theory of Belief Functions
ASB'03 Proceedings of the 1st international conference on Advanced Studies in Biometrics
How do correlation and variance of base-experts affect fusion in biometric authentication tasks?
IEEE Transactions on Signal Processing
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Having assessed the performance gains due to evidence fusion, previous works reported contradictory conclusions. For some, a consistent improvement is achieved, while others state that the fusion of a stronger and a weaker biometric expert tends to produce worst results than if the best expert was used individually. The main contribution of this paper is to assess when improvements in performance are actually achieved, regarding the individual performance of each expert. Starting from readily satisfied assumptions about the score distributions generated by a biometric system, we predict the performance of each of the individual experts and of the fused system. Then, we conclude about the performance gains in fusing evidence from multiple sources. Also, we parameterize an empirically obtained relationship between the individual performance of the fused experts that contributes to decide whether evidence fusion techniques are advantageous or not.