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Titlebook: Reliable Face Recognition Methods; System Design, Imple Harry Wechsler Book 2007 Springer-Verlag US 2007 3D.Performance.biometrics.computer

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Error Analysis,alysis explores here complementary objectives. First, for operational purposes, there is the acute need to predict performance in order to properly assess the utility in deploying a particular face recognition system. This is in sharp contrast to a technological evaluation that has access to ground
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e-Science and Computing, question addressed is how to combine the two kinds of minds Pascal talks about. The rapid increase expected in biometric data volumes is not matched by a commensurate increase in the quantity or quality of (data intensive) scientific research tools. To reach existing and future biometric challenges
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Introduction,to Wayman (I999) a suitable self-evident taxonomy will include cooperative vs. non-cooperative, overt vs. covert, habituated vs. non-habituated, attended vs. non-attended, standard vs. non-standard operating environments, and public vs. private.
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Data Collection,ilures that can be traced to image acquisition errors. The . is the expected proportion of the population for whom the system is unable to generate repeatable [signatures] templates, while the failure to acquire rate is defined as the expected proportion of transactions for which the system is unabl
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Face Recognition,s finds a mate for identification, the most similar one, even if there is none. Rejection, an option available only during open set face recognition, is appropriate for the case when there is no enrolled mate for the unknown probe.
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Face in a Crowd,h evidence that helps to disambiguate among alternative facial interpretations. Evidence accumulation, always watchful for change and ready to integrate it, is both progressive and adaptive. It is progressive because it is selective about what to look for and in what order, on one hand, and how to p
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