Fusion of face and voice using the Dempster-Shafer Theory for person verification

L. Mezai, F. Hachouf, Messaoud Bengherabi
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引用次数: 2

Abstract

In this paper, an algorithm for person verification is proposed. Dempster-Shafer Theory is used for face and voice fusion at the score level in order to overcome the limitations of unimodal biometric systems. Our experiments on the publicly available scores of the XM2VTS Benchmark database show a consistent improvement in performance compared to each individual modality. We have compared our approach with the sum rule and the likelihood ratio based fusion.
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使用Dempster-Shafer理论进行人脸和声音的融合,用于人的验证
本文提出了一种人的身份验证算法。为了克服单峰生物识别系统的局限性,Dempster-Shafer理论在分数水平上用于人脸和语音融合。我们在XM2VTS基准数据库的公开可用分数上的实验表明,与每种单独的模式相比,性能有一致的提高。我们已经将我们的方法与求和规则和基于似然比的融合进行了比较。
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