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als RSS Feed abonnieren📚 NIST Study Finds That Masks Defeat Most Facial Recognition Algorithms
💡 Newskategorie: IT Security Nachrichten
🔗 Quelle: science.slashdot.org
In a report published today by the National Institutes of Science and Technology (NIST), a physical sciences laboratory and non-regulatory agency of the U.S. Department of Commerce, researchers attempted to evaluate the performance of facial recognition algorithms on faces partially covered by protective masks. They report that even the best of the 89 commercial facial recognition algorithms they tested had error rates between 5% and 50% in matching digitally applied masks with photos of the same person without a mask. From a report: "With the arrival of the pandemic, we need to understand how face recognition technology deals with masked faces," Mei Ngan, a NIST computer scientist and a coauthor of the report, said in a statement. "We have begun by focusing on how an algorithm developed before the pandemic might be affected by subjects wearing face masks. Later this summer, we plan to test the accuracy of algorithms that were intentionally developed with masked faces in mind." The study -- part of a series from NIST's Face Recognition Vendor Test (FRVT) program conducted in collaboration with the Department of Homeland Security's Science and Technology Directorate, the Office of Biometric Identity Management, and Customs and Border Protection -- explored how well each of the algorithms was able to perform "one-to-one" matching, where a photo is compared with a different photo of the same person. (NIST notes this sort of technique is often used in smartphone unlocking and passport identity verification systems.) The team applied the algorithms to a set of about 6 million photos used in previous FRVT studies, but they didn't test "one-to-many" matching, which is used to determine whether a person in a photo matches any in a database of known images. Because real-world masks differ, the researchers came up with nine mask variants to test, which included differences in shape, color, and nose coverage.
Read more of this story at Slashdot.
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