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Cohort models are non-match models available in a biometric system. They could be other enrolled models in the gallery of the system. Cohort models have been widely used in biometric systems. A well-established scheme such as T-norm exploits cohort models to predict the statistical parameters of non-match scores for biometric authentication. They have also been used to predict failure or recognition...
Changes in illumination conditions can cause drastic variations in face appearance and affect the performance of a face authentication system. Near infrared (NIR) face imaging systems have been proposed as a promising way towards illumination invariant face verification. We show that when NIR face images cannot be observed, learning the relationship between NIR information and the corresponding visible...
While using more biometric traits in multimodal biometric fusion can effectively increase the system robustness, often, the cost associated to adding additional systems is not considered. In this paper, we propose an algorithm that can efficiently bound the biometric system error. This helps not only to speed up the search for the optimal system configuration by an order of magnitude but also unexpectedly...
Biometric performance assessment is made difficult by virtue of the fact that each user in the database introduces variability that cannot be controlled even with a well designed acquisition procedure and experimental protocol. As a result, the system performance is inevitably user-dependent. We propose explicitly to rank the users according to their performance using criteria such as the F-ratio,...
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