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A confidence-based late fusion framework for audio-visual biometric identification
Journal article   Peer reviewed

A confidence-based late fusion framework for audio-visual biometric identification

M.R. Alam, M. Bennamoun, R. Togneri and F. Sohel
Pattern Recognition Letters, Vol.52, pp.65-71
2015
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Abstract

This paper presents a confidence-based late fusion framework and its application to audio-visual biometric identification. We assign each biometric matcher a confidence value calculated from the matching scores it produces. Then a transformation of the matching scores is performed using a novel confidence-ratio (C-ratio) i.e., the ratio of a matcher confidence obtained at the test phase to the corresponding matcher confidence obtained at the training phase. We also propose modifications to the highest rank and Borda count rank fusion rules to incorporate the matcher confidence. We demonstrate by experiments that our proposed confidence-based fusion framework is more robust compared to the state-of-the-art late (score- and rank-level) fusion approaches.

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Citation topics
4 Electrical Engineering, Electronics & Computer Science
4.17 Computer Vision & Graphics
4.17.118 Face Recognition
Web Of Science research areas
Computer Science, Artificial Intelligence
ESI research areas
Engineering
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