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

• We propose a novel confidence ratio (C-ratio) to be used in score-level fusion.
• We propose a confidence factor to be used in rank-level fusion.
• Confidence-based late fusion improves the identification accuracy.
• Confidence-based late fusion performs better than the state-of-the-art.

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.