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Embedding quality measurements in multiple classifier fusionDr. Norman Poh Automatically verifying the identity of a person by means of biometrics (e.g., face and fingerprint) is an important application in our day-to-day activities such as accessing banking services and security control in airports. To increase the system reliability, several biometric devices are often used. This lecture considers how auxiliary information such as the quality associated with a biometric sample (quality measurements) and the device information can be used when combining the output of several biometric devices. Since both these sources of information are not discriminative in distinguishing genuine users from impostors, combining them is indeed a challenging problem. This lecture will illustrate how this problem can be solved using Bayesian networks and graphical models, combining, for instance, a clustering algorithm with a generative/discriminative classifier. |
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