A projection framework for biometrie scores fusion

This paper presents a projection framework for biométrie scores fusion. Essentially, the framework consists of a projection stage and a learning stage. Apart from investigating into several relatively new projection models for biométrie fusion, the projection stage attempts to unify these models into a single parametric structure. Three learning methods are investigated in conjunction with six projection models for their impacts on verification accuracy expressed in terms of equal error rate. An extensive experiment of these model and learning combinations on 32 fusion data sets are performed in the evaluation.

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