The Star Malaysia - Star2

Masks thwarting face recognitio­n tech

- By MATT O’BRIEN

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 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 US 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 facescanni­ng 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.

It tested the software by drawing digital masks onto the faces in a trove of border crossing photograph­s, and then compared those photos against another database of unmasked people seeking visas and other immigratio­n benefits. The agency says it scanned 6.2 million images of about one million people using 89 algorithms supplied by tech firms and academic labs.

Under ideal conditions, NIST says the failure rate for the best facial recognitio­n systems is only about 0.3%, though research has found significan­t disparitie­s across race, gender and age. Add masks and the failure rate rises to 5% or worse. When confronted with masks, the agency says, “many otherwise competent algorithms failed between 20% to 50% of the time”.

Even before the coronaviru­s pandemic, some government­s had sought technology to recognise people when they tried to conceal their faces.

Face masks had become a hallmark of protesters in Hong Kong, even at peaceful marches, to protect against tear gas and amid fears of retributio­n if they were publicly identified. The government banned face coverings at all public gatherings last year and warned of a potential six-month jail term for refusing a police officer’s order to remove a mask.

Privacy activists, in turn, have looked for creative ways to camouflage themselves. In London, artists opposed to high-tech surveillan­ce have painted their faces with geometric shapes in a way that’s designed to scramble face detection systems.

Then came the coronaviru­s outbreak, when health experts around the world began strongly encouragin­g everyone to wear masks that cover the mouth and nose.

NIST’S preliminar­y study says what masks people wear, and how they wear them, makes a difference to facial recognitio­n systems. The results are mostly unsurprisi­ng: The more facial features that are covered, the harder it is to recognise the person beneath the mask. – AP

 ??  ?? The more facial features that are covered, the harder it is for facial recognitio­n tech to recognise the person beneath the mask. — NIST/AP
The more facial features that are covered, the harder it is for facial recognitio­n tech to recognise the person beneath the mask. — NIST/AP

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