Coronavirus is spreading all over the world taking more lives every day and putting economies of whole countries “on hold”. If we are to compare a country with an organism, the disease has already infiltrated, and all that remains is to wait it out. Every human being, akin to a diseased cell, humbly produces millions of the virus’s copies, increasing the risk of infection for others. Fortunately, unlike the helplessly obedient cells, we have the tools to control the severity of this disease.
One of the most powerful tools capable of containing the infection is the face recognition technology together with the FindFace Multi solution based on it. But how can a non-medical technology fight a viral infection? Indeed, the battle with the coronavirus itself will be entrusted to microbiologists and epidemiologists who are currently working hard in laboratories and hospitals worldwide. Facial recognition, in turn, can play a crucial role in limiting the number of infected.
How does it work?
So far, South Korea has been the most successful in curbing the spread of infection. Thanks to an existing face recognition system powering the CCTV cameras in major cities, the South Korean government has been able to strike at the heart of the problem and effectively reduce the number of infected in the shortest time frame. In Russia, the government of Moscow is in the process of deploying a system that is intended to track the movements of the patients with a confirmed diagnosis and all those they come in contact with. Among position and transaction tracking, this system includes a facial recognition software provided by NtechLab.
As they say, desperate times call for desperate measures and, unfortunately, without the isolation of the confirmed infected or potential coronavirus carriers, it will be impossible to ensure the safety of citizens throughout the city and country. Facial recognition systems are the only way to reduce the number of infected people without the need to mobilize public services. Home-quarantined people are simply added to special lists, allowing the system to instantly notify operators of any violations. Besides that, it is easy to track in real time who has been in contact with the quarantined person and take appropriate measures.
With the help of cameras connected to the recognition system it is also possible to collect impersonal statistical information to monitor quarantine areas in the form of squares, parks, individual houses or entrances. Thanks to the silhouette counting function, the respective services will be able to enhance security in the event of mass violations within such zones. Such a city-wide system will be able to provide information on when and where the infected individual was throughout the day, and even if he was wearing a medical mask.
Have you noticed how dramatically the number of people wearing masks and respirators has increased in the city streets? Although the cause of this phenomenon is obvious, people’s motives can vary greatly. Someone is seriously concerned about the health of surrounding people, someone sees this as an opportunity to complete the image of the city ninja without turning heads, and someone hides the face in hopes to escape from responsibility for illegal acts. In China, for example, the indiscriminate spread of masks among the population has plunged widely used facial recognition systems into chaos, which in a pandemic situation can only add problems.
The FindFace Multi solution is protected from this kind of collapse, as it recognizes faces with high precision, even with masks, scarves, glasses and other elements that partially hide facial features. It’s all about a revolutionary neural network algorithm that creates a vector of each face’s characteristics and compares it with those in the database. Each vector is unique, and even if a part of it cannot be revealed because of hindrances, the person will still be recognized with the available features. Furthermore, the system can determine if a medical mask is on the face and if it is worn correctly. The effectiveness of the system has been repeatedly proven in international The effectiveness of the system has been repeatedly proven in international tests, such as the one held by the National Institute of Standards and Technology (NIST).
Recent versions of the system have been supplemented by a number of innovations directly aimed at combating the COVID-19 epidemic. FindFace is now able to recognize not only faces, but also silhouettes with high precision. In case of an epidemiological situation getting out of control, it is possible to detect contacts and analyze social connections by searching through history. In this way, it is possible to localize the circle of potentially infected people and take quarantine measures more accurately, while caring of the health of those who are ill and minimizing the inconvenience to those who are healthy. Currently, face recognition is the only effective method of social monitoring in a city environment, significantly superior to geolocation methods.
A key advantage of facial recognition technology is that it requires no contact, which is something that other biometric control systems, for example, working with fingerprints, cannot boast. In the current situation, such systems rather play into the hands of the coronavirus and its spread among the masses. The universal introduction of facial biometrics systems for access control will also help in the fight against the pandemic. In addition, it is possible to work simultaneously with systems for measuring body temperature remotely.
The FindFace facial recognition system from NtechLab will be able to work reliably in difficult conditions and ensure the health and safety of the citizens without involving additional forces. In the future, such systems will make it possible to reduce any viral threats to zero, allowing to isolate infected people on the spot without the chance of further spread.
Interested in the intricacies of the face recognition system designed to prevent the spread of COVID-19? Learn exactly how FindFace aids in the fight against the pandemic.