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Titlebook: Biometrics and Identity Management; First European Works Ben Schouten,Niels Christian Juul,Massimo Tistarel Conference proceedings 2008 Spr

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An Empirical Comparison of Individual Machine Learning Techniques in Signature and Fingerprint Classuantitatively how performance is related to classifier type, and also provide a finer-grained analysis to relate performance to specific non-biometric factors in population demographics. The paper discusses the implications for individual modalities, for multiclassifier but single modality systems, and for full multibiometric solutions.
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Quality-Based Score Normalization and Frame Selection for Video-Based Person Authenticationes in biometric authentication is exposed. Two different quality-based score normalization techniques are derived from this theoretical framework. Furthermore, a quality-based frame selection technique and a new face image quality measure are also presented. The ability of this quality measure and t
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On Quality of Quality Measures for Classificationsignal quality measures in classification. While an ideal signal quality measure should be a precise quantification of the actual signal properties relevant to the classification process, a real quality measurement may be uncertain. We show how does the degree of uncertainty in quality measurement i
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Modeling Marginal Distributions of Gabor Coefficients: Application to Biometric Template Reductionge amount of data that must be stored. One way to reduce space is to quantize Gabor coefficients using an accurate statistical model which should reflect the behavior of the data. Statistical image analysis has revealed one interesting property: the non-Gaussianity of marginal statistics when observ
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Bosphorus Database for 3D Face Analysisaper. This database is unique from three aspects: i) the facial expressions are composed of judiciously selected subset of Action Units as well as the six basic emotions, and many actors/actresses are incorporated to obtain more realistic expression data; ii) a rich set of head pose variations are a
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