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Facial recognition

Can facial recognition unlock the phone while wearing a mask?

Wearing a face mask becomes perfectly normal in response to a viral respiratory infection epidemic. In fact, with a risk of becoming infected anytime, anywhere—be it in public transport, in the theater, in the store, or at a dinner party—a face mask is gradually moving into the category of life-sustaining items, such as clothes. Leaving the house in the midst of an epidemic without a face mask can be translated as bad form. In contrast, wearing a face mask is seen as a sign of self-preservation and concern for the health and safety of others around you. And we are not aiming at covering our faces here in doing so—that’s just a side effect. Well, sort of. Facial recognition on smartphone

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Does not this make you wonder what the future of recognition technologies might look like when everybody is wearing a mask that covers a large part of their faces?

In the “Internet of Everything” era, face recognition systems have become, if not the core, a very important element of public safety, target marketing, and social interactions in general. They are now integral parts of city infrastructure—security cameras are hidden in areas where you won’t even suspect them to be, such as streets, airports, grocery stores, hotels, or sports stadiums. They are there not only to prevent crime by tracking unsavory characters but also to contribute to the effectiveness of targeted sales and advertising through “knowing your customer”. It seems like KYC has taken on a somewhat more literal meaning.

Face Recognition Struggles: Masked Faces Disrupt Algorithm Accuracy

For most face recognition algorithms to work, the person has to be barefaced, because those algorithms evaluate the face “as a whole”. When the face recognition system spots a medical mask or respirator on the human face, it will most likely respond with “face is covered”, and refuse further recognition attempts. The chance of recognition failure is even higher in cases where there are some decorative elements on the mask, such as prints or texture; it could be an abstract pattern, or a jaw, or Darth Vader’s helmet. It is obvious that during systems testing, the developers did not plan for the scenario in which every city dweller wears a face mask; as a result, the implications that have been described are not prevented. However, such a scenario does not seem to sound that surprising anymore.

Face recognition systems will quite obviously become useless if the majority of people start protecting themselves with a face mask—unless we see some major improvements in the algorithms of those systems, of course. Not only that, relying on them could be dangerous since the percentage of false positives might increase sharply, which will inevitably lead to malfunctions.

Recognition technologies will certainly be further developed, algorithms will change, and it is conceivable that we will soon witness the emergence of a solution that will be able to provide recognition results at a fairly acceptable standard with only the uncovered part of the face. Those results could then be taken into account in the decision-making process. As of now, the flow of information on the coronavirus epidemic is not only leading to the collapse of cross-border online trade, but it has also significantly affected those sectors that have just started getting accustomed to face recognition systems and the development of face recognition technology itself.

According to the Russian satellite news agency on March 11, many developers of facial recognition systems are researching new algorithms, hoping to recognize faces under medical masks.

“This is a difficult problem for most face recognition algorithms,” Alexander Minin, general manager of Russian face recognition technology developer N-Tech.Lab, told Satellite News Agency. “Some of the industry leaders are urgently upgrading algorithms. Strive to come up with a solution that will ensure recognition (facial features) even when the face is mostly obscured. “

Advancements in Facial Recognition: Identifying Individuals Despite Masks and Complex Headwear

Minin said that their goal is to be able to identify people regardless of lighting and weather conditions and whether or not the identified person looks at the camera. At present, N-Tech Lab’s technology can recognize human faces even if they are covered 40% by masks, motorcycle helmets, and complicated headwear.

A Chinese company says it has developed the country’s first facial recognition technology that can identify people when they are wearing a mask, as most are these days because of the coronavirus, and help in the fight against the disease. China employs some of the world’s most sophisticated systems of electronic surveillance, including facial recognition.

But the coronavirus, which emerged in Hubei province late last year, has resulted in almost everyone wearing a surgical mask outdoors in the hope of warding off the virus, posing a particular problem for surveillance.

Now Hanwang Technology, which also goes by the English name Hanvon, said it has come up with technology that can successfully recognize people even when they are wearing masks.

“If connected to a temperature sensor, it can measure body temperature while identifying the person’s name, and then the system would process the result, say, if it detects a temperature over 38 degrees,” Hanwang Vice President Huang Lei said in an interview.

Key Aspects of Facial Recognition Technology in Smartphones: Benefits, Concerns, and Implications Facial recognition on smartphone

  1. Enhanced Security: Facial recognition on smartphones offers an additional layer of security. It’s a biometric method that is hard to fool, making your device safer from unauthorized access.
  2. Convenience: It provides a seamless and quick way to unlock your device, eliminating the need to remember complex passwords or patterns.
  3. App Authentication: Some apps, particularly banking and payment apps, use facial recognition for authentication, ensuring secure transactions.
  4. Personalized Experiences: Certain apps use facial recognition to personalize the user experience, such as social media filters or virtual makeup trials.
  5. Privacy Concerns: While it enhances security, facial recognition also raises privacy concerns. The data, if not stored securely, can be misused.
  6. Dependence on Hardware: The effectiveness of facial recognition depends on the quality of the smartphone’s camera and sensors.
  7. Lighting Conditions: Facial recognition may struggle in poor lighting conditions or if the face is partially covered.
  8. Continuous Learning: Many systems learn and improve their recognition capabilities over time, becoming more accurate the more they’re used.
  9. Potential for Bias: There have been concerns about racial and gender bias in facial recognition technology, which developers need to address.
  10. Legal and Ethical Implications: The use of facial recognition technology involves various legal and ethical implications that are still being explored and debated.

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