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TECHNOLOGY – Face recognition software making progress at recognizing masked faces (OODA)

The NIST has found that facial recognition algorithms have improved their ability to detect identities even when the individual is wearing a mask. Since the beginning of the pandemic, numerous studies have been conducted to test the effect of masked faces on algorithms, as facial recognition software pre-pandemic was unable to identify masked individuals. According to the NIST, some error rates decreased as much as by a factor of 10 between pre and post COVID algorithms.

NIST stated that in the best cases, software algorithms are making errors only 2.4-5% of the time on masked faces, which is comparable to the performance of the technology in 2017 with clear, full-face photos. The study accumulated 65 newly submitted algorithms that were tested, offering results for 152 total algorithms to present a full picture of the technology’s capabilities.

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