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Score normalization in stratified biometric systems

机译:分层生物识别系统中的分数归一化

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Stratified biometric system can be defined as a system in which the subjects, their templates or matching scores can be separated into two or more categories, or strata, and the matching decisions can be made separately for each stratum. In this paper we investigate the properties of the strat-ifiedbiometric system and, in particular, possible strata creation strategies, score normalization and acceptance decisions, expected performance improvements due to stratification. We perform our experiments on face recognition matching scores from IARPA Janus CS2 dataset.
机译:分层生物识别系统可以定义为一种系统,在该系统中,受试者,其模板或匹配分数可以分为两个或多个类别或层次,并且可以针对每个层次分别做出匹配决策。在本文中,我们研究了分层生物计量系统的属性,尤其是可能的分层创建策略,分数归一化和接受决策,由于分层而带来的预期性能改进。我们对来自IARPA Janus CS2数据集的面部识别匹配分数进行了实验。

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