Predicting Performance in Large-Scale Identification Systems by Score Resampling
نویسندگان
چکیده
In this paper we investigate the problem of predicting the closed set identification performance of biometric matchers in large-scale applications given their corresponding performances in small-scale applications. We identify two major effects responsible for the prediction errors in previously proposed methods: the binomial approximation effect and the score mixing effect. We propose to use a score resampling method for prediction, which is not susceptible to the binomial approximation effect. We also reduce score mixing effect by using score selection based on identification trial statistics. The experiments on NIST biometric score dataset show the accuracy of our proposed prediction method.
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