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- W2941516811 abstract "This research discusses the evaluation of biometric systems that are designed to process hundreds to tens of thousands of individuals in short time spans. We propose a method for evaluating a system's performance across capture attempts for the purpose of identifying characteristics that are advantageous in these high-throughput environments. We also present a novel modification to the traditionally accepted biometric performance metrics of failure-to-acquire, and true-match rate. Namely, this paradigm shift holds that these metrics are a function of time and, as such, vary with the time available for a biometric system to interact with a user. This research demonstrates the utility of these time-based metrics in evaluating the performance of multiple, commercially available, high-throughput systems. We show that different biometric systems have notably different time-based performance curves using a corpus of data collected during the 2018 Department of Homeland Security, Science and Technology Directorate (DHS S&T) Biometric Technology Rally. These curves and the deviations between them are useful when quantifying the suitability of a technology, evaluated via scenario testing, for deployment in an operational environment where the throughput of the target population is a key performance parameter." @default.
- W2941516811 created "2019-05-03" @default.
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- W2941516811 date "2018-10-01" @default.
- W2941516811 modified "2023-09-25" @default.
- W2941516811 title "On Efficiency and Effectiveness Tradeoffs in High-Throughput Facial Biometric Recognition Systems" @default.
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- W2941516811 doi "https://doi.org/10.1109/btas.2018.8698598" @default.
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