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The decrease of representativeness of available templates during time is due to the large intra-class variations characterizing biometrics (e.g. faces). This requires the design of algorithms able to make biometric verification systems adaptive to such variations. Among others, the template co-update algorithm, which uses the mutual help of two complementary biometric matchers, has shown promising experimental results. The present paper is aimed to describe a theoretical model able to explain the co-update behaviour. In particular, the focus is on the relationships between error rate and gallery size increase. Preliminary experimental results are shown to validate the proposed model

Modelling FRR of Biometric Verification Systems Using the Template Co-update Algorithm