Template co-update in multimodal biometric systems

Performances of biometric recognition systems can degrade quickly when the input biometric traits exhibit substantial variations compared to the templates collected during the enrolment stage of users. This issue can be addressed using template update methods. In this paper, a novel template update method based on the concept of biometric co-training is presented. In multimodal biometric systems, this method allows co-updating the template galleries of different biometrics, realizing a co-training process of biometric experts which allows updating templates more quickly and effectively. Reported results provide a first experimental evidence of the effectiveness of the proposed template update method.