分层生物识别系统的评分归一化

S. Tulyakov, Nishant Sankaran, S. Setlur, V. Govindaraju
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引用次数: 0

摘要

分层生物识别系统可以定义为将受试者、其模板或匹配分数分为两个或两个以上的类别或层次,并对每个层次分别进行匹配决策的系统。在本文中,我们研究了层化生物识别系统的特性,特别是可能的地层创建策略,评分规范化和接受决策,由于分层而预期的性能改进。我们对IARPA Janus CS2数据集的人脸识别匹配分数进行了实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Score normalization in stratified biometric systems
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.
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