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Conventional verification systems, such as those controlling access to a secure room, do not usually require the user to reauthenticate himself for continued access to the protected resource. This may not be sufficient for high-security environments in which the protected resource needs to be continuously monitored for unauthorized use. In such cases, continuous verification is needed. In this paper, we present the theory, architecture, implementation, and performance of a multimodal biometrics verification system that continuously verifies the presence of a logged-in user. Two modalities are currently used—face and fingerprint—but our theory can be readily extended to include more modalities. We show that continuous verification imposes additional requirements on multimodal fusion when compared to conventional verification systems. We also argue that the usual performance metrics of false accept and false reject rates are insufficient yardsticks for continuous verification and propose new metrics against which we benchmark our system.
Pattern recognition, biometrics, fusion, verification.

T. Sim, S. Zhang, R. Janakiraman and S. Kumar, "Continuous Verification Using Multimodal Biometrics," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 29, no. , pp. 687-700, 2007.
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