The future of facial recognition technology may depend on one very specific part of the face: the area around the eyes.

Before the global pandemic, facial recognition systems typically worked by comparing measurements between different facial features in one image to those in another picture. But when you’re wearing a mask over your nose, mouth, and cheeks, you’re offering up a fraction of the information normally used to figure out your identity.

Now, numerous facial recognition companies say they are focusing on better identifying people based on the portion of the face above the nose and, in particular, the eye region. The stakes are high to get it right, and soon.

Facial recognition technology has grown in prevalence — and controversy — in recent years, popping up everywhere from airport check-in lines to police departments and drugstores. And it may become even more popular as businesses look to contact-free security options because of the pandemic. Yet while it could add a sense of security and convenience for businesses who roll it out, the technology has been widely criticized by privacy advocates for built-in racial biases and potential for misuse.

A late July report on facial recognition algorithms and masked faces by federal researchers at the National Institute of Standards and Technology, or NIST, confirmed that many pre-Covid algorithms were not up to the task. The most accurate facial recognition algorithms that the lab tested failed to make a correct match between 5% and 50% of the time.

There was one key caveat, however: All the algorithms NIST tested were submitted before mid-March. In the months since then, a number of artificial intelligence companies have said they’re working to ensure their facial recognition technology can figure out who is behind the mask.

This spring, as the pandemic worsened, Tech5 cofounder Rahul Parthe started getting questions from customers about masks. Specifically, they wanted to know whether the accuracy of Tech5’s facial-recognition software would be hampered by facial coverings.

Tech5, which is based in Geneva, Switzerland, sells face, fingerprint and iris-recognition technologies to customers ranging from healthcare companies to law enforcement. Even before the pandemic, Parthe said, the company’s technology had to deal with recognizing partly concealed faces, whether by religious face coverings or masks, which have been fairly common in southeast Asia for years.

Nonetheless, its facial recognition technology appeared to perform worse with a mask — at least for the Tech5 algorithm NIST tested. The algorithm ranked in the top 10 on NIST’s list, but it was still better at identifying non-masked faces than masked ones. Parthe said this algorithm was designed to identify someone who might be wearing big sunglasses or sporting facial hair they didn’t have on a stored picture; it was not specifically meant to deal with face masks.

Even before COVID, Parthe said, the company was researching recognition technology that concentrates on the eyes and forehead, which it wants to combine with iris recognition to identify people. (Iris recognition requires a special scanner and tends to cost more than facial recognition.) Now, with an increasing number of requests for facial recognition software that works well with masks, TECH5 is working on a new algorithm that will ignore the face below the nose in a picture.

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