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An Investigation of High-Throughput Biometric Systems: Results of the 2018 Department of Homeland Security Biometric Technology Rally

机译:高通量生物识别系统的调查:2018年国土安全部生物识别技术集会的结果

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The 2018 Biometric Technology Rally was an evaluation, sponsored by the U.S. Department of Homeland Security, Science and Technology Directorate (DHS S&T), that challenged industry to provide face or face/iris systems capable of unmanned, traveler identification in a high-throughput security environment. Selected systems were installed at the Maryland Test Facility (MdTF), a DHS S&T affiliated bio-metrics testing laboratory, and evaluated using a population of 363 naive human subjects recruited from the general public. The performance of each system was examined based on measured throughput, capture capability, matching capability, and user satisfaction metrics. This research documents the performance of unmanned face and face/iris systems required to maintain an average total subject interaction time of less than 10 seconds. The results highlight discrepancies between the performance of biometric systems as anticipated by the system designers and the measured performance, indicating an incomplete understanding of the main determinants of system performance. Our research shows that failure-to-acquire errors, unpredicted by system designers, were the main driver of non-identification rates instead of failure-to-match errors, which were better predicted. This outcome indicates the need for a renewed focus on reducing the failure-to-acquire rate in high-throughput, unmanned biometric systems.
机译:2018年生物识别技术拉力赛是一项由美国国土安全部科学技术局(DHS S&T)赞助的评估,该挑战对行业提出挑战,要求其提供能够在高通量安全性下实现无人,旅行者身份识别的面部或面部/虹膜系统环境。选定的系统安装在DHS S&T附属的生物特征测试实验室Maryland Test Facility(MdTF)中,并使用从一般公众中招募的363位天真的人类受试者进行评估。根据测得的吞吐量,捕获能力,匹配能力和用户满意度指标来检查每个系统的性能。这项研究记录了无人脸和面部/虹膜系统的性能,这些系统可将受试者的平均总互动时间保持在10秒以内。结果突出显示了系统设计人员所预期的生物识别系统的性能与测得的性能之间的差异,表明对系统性能的主要决定因素不完全了解。我们的研究表明,系统设计师无法预测的失败获取错误是导致非识别率的主要驱动力,而不是失败匹配错误的主要原因,后者可以更好地进行预测。这一结果表明,需要重新关注降低高通量,无人值守生物识别系统中的失败获取率。

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