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Cascading multimodal verification using face, voice and iris information

By Ping-han Lee, Lu-jong Chu, Yi-ping Hung, Sheng-wen Shih, Chu-song Chen and Hsin-min Wang


In this paper we propose a novel fusion strategy which fuses information from multiple physical traits via a cascading verification process. In the proposed system users are verified by each individual modules sequentially in turns of face, voice and iris, and would be accepted once he/she is verified by one of the modules without performing the rest of the verifications. Through adjusting thresholds for each module, the proposed approach exhibits different behavior with respect to security and user convenience. We provide a criterion to select thresholds for different requirements and we also design an user interface which helps users find the personalized thresholds intuitively. The proposed approach is verified with experiments on our in-house face-voice-iris database. The experimental results indicate that besides the flexibility between security and convenience, the proposed system also achieves better accuracy than its most accurate module. 1

Year: 2007
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