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Multi-modal biometric fusion is more accurate and reliable compared to recognition using a single biometric modality. However, most existing fusion approaches neglect the influence of the qualities of the biometric samples in information fusion. Our goal is to advance the state-of-the-art in biometric fusion technology by providing a more universal and more accurate solution for personal identification...
This paper addresses the problem of developing facial image quality metrics that are predictive of the performance of existing biometric matching algorithms and incorporating the quality estimates into the recognition decision process to improve overall performance. The first task we consider is the separation of probe/gallery qualities since the match score depends on both. Given a set of training...
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