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Technology Face masks are thwarting even the best facial recognition algorithms, study finds

01:20  28 july  2020
01:20  28 july  2020 Source:   cnet.com

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They report that even the best of the 89 commercial facial recognition algorithms tested had error rates between 5% and 50% in matching digitally applied face masks with photos of the same person without a mask . “With the arrival of the pandemic, we need to understand how face recognition

In the parts of China where medical face masks are mandatory, some find that the facial recognition systems they use to unlock their phones don't work. But it’s also making life difficult for people who rely on facial recognition to do simple things like unlock their phones, access their bank accounts

It turns out face masks aren't just effective for preventing the spread of airborne diseases like COVID-19 -- they're also successful at blocking facial recognition algorithms, researchers found.

a group of people standing on a mask posing for the camera: NIST digitally added face masks to immigrations photos to test 89 facial recognition algorithms. NIST © Provided by CNET NIST digitally added face masks to immigrations photos to test 89 facial recognition algorithms. NIST

In a report published on Monday, the US' National Institute of Standards and Technology, or NIST, found that face masks were thwarting even the most advanced facial recognition algorithms. Error rates varied from 5% to 50%, depending on the algorithm's capabilities.

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Few facial recognition systems today recognize people wearing face masks , but some of the first to do so have emerged in China in recent weeks. To create its face mask data set, Hanwang asked its employees to share photos of themselves wearing face masks . Based on those photos, the company

He knew that researchers have found that facial - recognition software exhibits racial biases. The programs are often best at identifying white and male Even without a mask , though, you can confuse some facial - recognition programs by obscuring parts of your face with makeup, costuming, hairdos

Those results are troubling for the facial recognition industry, which has been scrambling to develop algorithms that can identify people through their eyes and nose alone as more and more people turn to face masks to prevent the spread of the coronavirus outbreak.

Face masks are essential tools to limit the disease's spread, with governments in the majority of US states requiring people to wear coverings during the pandemic. The masks have caused trouble for facial recognition software, prompting companies like Apple to push an update so Face ID can still work even when people are wearing covers.

Facial recognition algorithms rely on getting as much data points on a person's image as possible, and face masks tend to take away a lot of valuable information they need to identify a person. The algorithms are already sensitive enough that improper lighting or a bad angle is enough to fool the technology, and the face masks make matters worse, the study found.

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Face masks are mandatory in at least two provinces in China, including the city of Wuhan. It turns out that face masks trip up facial recognition -based functions, a technology necessary for many Facial recognition is even used in restrooms to prevent an occupant from taking too much toilet paper.

Software engineers work on a facial recognition system that identifies people when they wear a face mask at the development lab of the Chinese electronics manufacturer Hanwang. Hanwang is now selling two main kinds of products that use the new technology.

a group of people standing on a mask posing for the camera: NIST digitally added face masks to immigrations photos to test 89 facial recognition algorithms. © NIST

NIST digitally added face masks to immigrations photos to test 89 facial recognition algorithms.

One algorithm that would have an error rate of 0.3% surged to a 5% when presented with images of people wearing masks, the study found. The study tested the effectiveness of 89 facial recognition algorithms against face masks.

The test looked at the algorithms' "one-to-one" matching capabilities -- essentially comparing one photo of a person to a different picture, but with a mask on. NIST used 6 million images for its research, and applied masks on digitally, with different variations of the coverings.

The study also found that the more of the nose that was covered, the more likely it was to thwart the algorithms. Black masks were also more likely to fool the algorithms than blue ones, the research showed.

NIST said this was the first of an ongoing series of tests surrounding facial recognition and face masks, and it plans to test algorithms that were created specifically for coverings later this summer.

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Face masks are a symbol of the pandemic era – a visual metaphor for the tiny, unseen viral foe that They found a standard surgical face mask was enough to considerably reduce the amount of virus Facial hair can also affect their performance as it disrupts the seal. The US Centers for Disease

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"With the arrival of the pandemic, we need to understand how face recognition technology deals with masked faces," said Mei Ngan, a NIST researcher behind the report. "We have begun by focusing on how an algorithm developed before the pandemic might be affected by subjects wearing face masks."

Ngan said NIST expects algorithms to improve with detecting people wearing face masks in the future.

Facial recognition researchers have been compiling photos of people wearing face masks as data for its algorithms to learn from -- in some cases, without people's knowledge.

The NIST study used photos of people applying for immigration benefits and digitally altered mask photos of travelers entering the US, according to the report.

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usr: 3
This is interesting!