Face recognition designed to detect around face masks fails, research found

For the latest news and information about the coronavirus pandemic, WHO website..

Many face recognition companies claim to be able to identify people with pinpoint accuracy While they are wearing face masks, However Latest research results It shows that the cover dramatically increases the error rate.

In Tuesday’s update, the National Institute of Standards and Technology examines 41 face recognition algorithms submitted after the COVID-19 pandemic was declared in mid-March. Many of these algorithms were designed with a face mask in mind and claimed to be able to accurately identify a person even when half of the face was covered.

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In July, NIST published a report pointing out that face masks interfered with normal face recognition algorithms. Error rates ranging from 5% to 50%.. NIST is widely acknowledged to be the leading authority on face recognition accuracy tests, and algorithms are expected to improve the identification of people in face masks.

With the advent of masks, the day has yet to come, as all algorithms increase error rates by at least a little bit. Some algorithms were still accurate overall, such as the error rate of Chinese face recognition company Dahua’s algorithm rising from 0.3% without mask to 6% with mask, while other algorithms have errors up to 99% It was a rate.

Rank 1, face recognition provider Used in cities like Detroit, The error rate without mask was 0.6%, and after applying the mask digitally, the error rate was 34.5%. In May, the company launched. “Peripheral recognition]. It claimed to be able to identify people just outside the eyes and nose.

Rank 1 CEO Brendan Klare said he was unable to send the algorithm to NIST because he was limited to one send per organization.

“Thus, the NIST mask study does not reflect our ability to perform identification in the presence of masks,” Claire said in an email.

TrueFace, that is Used in school Also, at Air Force Base, the addition of masks increased the error rate of the algorithm from 0.9% to 34.8%. Sean Moore, CEO of the company, Told CNN on August 12 The researchers were working on a better algorithm for detecting beyond the mask.

The two companies did not respond to requests for comment.

The additional masks increase the error rate of all face recognition algorithms, but some have low error rates as low as 3%. This shows that the algorithm is not incapable of identifying a person, even if the face is covered.

Face masks are a proven tool to limit the spread of new coronaviruses and are owned by governments around the world Compulsory people wear covers To reduce the impact of outbreaks. Medical professionals Wear masks for yearsEncourage face recognition companies to improve their algorithms.

NIST publishes a continuous report on how the mask used the 6 million images in the database and digitally added the mask to the photo to see how the mask affected the face recognition algorithm.

Physical masks have a variety of shadings, textures, and patterns, and can also confuse algorithms, so if NIST used a photo of a real person in the mask instead of a digitally added cover. , The error rate may be high.

The information contained in this article is for educational and informational purposes only, not for health or medical advice. If you have any questions about your medical condition or health goals, always consult your doctor or other qualified healthcare provider.

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