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

TitleAn Investigation of High-Throughput Biometric Systems: Results of the 2018 Department of Homeland Security Biometric Technology Rally
Publication TypeConference Paper
Year of Publication2018
AuthorsHoward, J. J., Blanchard, A. J., Sirotin, Y. B., Hasselgren, J. A., Vemury, A. R.
Conference Name2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS)
Date PublishedOct. 2018
ISBN Number978-1-5386-7180-1
Keywords2018 Biometric Technology Rally, capture capability, DHS S-T affiliated bio-metrics, Face, face-iris systems, high-throughput biometric systems, high-throughput security environment, homeland security biometric technology rally, Iris recognition, Maryland Test Facility, matching capability, MdTF, measured performance, measured throughput, Measurement, Metrics, metrics testing, National security, pubcrawl, Science and Technology Directorate, security of data, Terrorism, Testing, Throughput, traveler identification, U.S. Department, unmanned biometric systems, unmanned face, US government, user satisfaction metrics

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.

Citation Keyhoward_investigation_2018