Even the best commercial facial recognition systems have error rates as high as 50% when trying to identify masked faces, says study.
Having a tough time recognising your neighbours behind their pandemic masks? Computers are finding it more difficult, too.
A preliminary study
published by a US
agency on Monday found that even the best commercial facial recognition
systems have error rates as high as 50% when trying to identify masked faces.
The mask problem is why
Apple earlier this year made it easier for iPhone owners to unlock their phones
without Face ID. It could also be thwarting attempts by authorities to identify
individual people at Black Lives Matter protests and other gatherings.
The National
Institute of Standards and Technology says it is launching an investigation
to better understand how facial recognition performs on covered faces. Its
preliminary study examined only those algorithms created before the pandemic,
but its next step is to look at how accuracy could improve as commercial providers
adapt their technology to an era when so many people are wearing masks.
Some companies, including
those that work with law enforcement, have tried to tailor their face-scanning
algorithms to focus on people's eyes and eyebrows.
NIST, which is a part of
the Commerce Department, is working with the US Customs and Border Protection
and the Department of Homeland Security's science office to study the problem.
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