Without realizing it, you have already tried this technology on your cell phone, tablet, or even to enter specific applications. But… do you know what facial recognition is and how it works?
Do you know all the uses that can be given to it? Don’t worry; you are in the right place to answer all these questions.
Facial recognition is a technology that makes it possible to identify or verify a person’s identity through their face.
Current facial recognition systems are based on Artificial Intelligence and deep neural networks that allow determining with an almost unerring accuracy if two images correspond to the same person. Identification can also be performed, indicating whether an individual is in a specific database through a picture of that person.
*Images compared with the Veridas das-Face biometric engine.
Facial recognition systems use facial biometrics to allow people to prove their identity securely. In the same way that our family or acquaintances recognize us by our faces, facial recognition systems will enable us to verify ourselves by who we are without the need to carry a credential or remember a password.
Facial recognition systems, therefore, have two main functions:
The fundamental goal of facial recognition systems is to provide a faster and more secure way to confirm a person’s identity. The use of facial biometrics improves both the user experience and the security of the process. On the one hand, users do not have to remember passwords and credentials. On the other hand, people’s real identity is verified since biometrics are unique to each individual, whereas credentials can be shared, lost, or stolen.
Yes, facial recognition systems are much more secure than current passwords and OTPs (One Time Passwords) since both still represent something that people know and, therefore, we can forget. Others can also know or quickly find out.
The Payment Services Directive (PSD2) of the European Union defines three levels of security or ways in which we can verify our identity:
Biometric recognition systems allow people to be credited for what they are, for their inherent elements and therefore represent the safest way to verify our identity.
Before understanding how biometric authentication works, it is necessary to understand how the facial biometric engines behind facial recognition software work.
A biometric engine transforms the image captured during verification into a biometric vector through Artificial Intelligence algorithms. A biometric vector is a set of coordinates constructed from the unique characteristics of a person’s face.
In the past, engineers designed vectors by hand based on the distance between characteristic points of the face (distance between the nose and the mouth, between the eyes, etc.). Today, artificial neural networks can learn by themselves from millions of examples and are much more accurate.
Therefore, when performing biometric authentication, the system compares mathematical vectors, not images. It is essential to understand this nuance because the servers of companies using a facial recognition system do not store pictures but keep these biometric vectors.
These vectors are irreversible (you cannot return to the original image) and are not interoperable (other facial recognition systems cannot use them).
Thus, a biometric vector is generated when a person registers for the first time in the system. Later, when they want to operate, they will retake a photo, which will be transformed into another vector. This will be compared against the registration vector to determine if it is the same person.
The high level of development of these technologies allows this process to be carried out in real-time and practically instantaneous for the user.
Believe it or not, facial recognition is more than 50 years old. In the mid-1960s, a research team used a very rudimentary scanner to map biometric data such as hairline and eye or nose location. However, at that time, it was not successful at all.
In the following decades, the rudimentary computers at the time continued to be tested, but computers found it easier to beat chess grandmasters than to recognize human faces.
The main problem with these systems was their traceability, i.e., the possibility of reconstructing the original image. In addition, they were very fragile to changes in appearance, such as a beard or the use of glasses or a mask.
In recent years, biometrics engines have been developed with Artificial Intelligence. These systems are trained to learn to recognize faces like the human brain, able to distinguish a person in different circumstances and with greater accuracy due to the infinity of data they process.
Current systems have accuracy rates of over 99% for databases of millions of faces. Therefore, they are much more reliable than humans in identifying a person.
*Images compared with the Veridas das-Face biometric engine.
Facial recognition systems based on Artificial Intelligence make it possible to verify a person’s real identity by linking that identity with an inherent and unique element of human beings, their face. These technologies’ advances in the last decades offer an accuracy greater than 99%.
This identity verification option makes the process much faster and easier. Users can do it from a mobile device or computer at any time and place without needing to go anywhere in person or forgetting forgotten passwords or credentials.
As we have already mentioned, the uses of facial recognition are enormous and very diverse. Moreover, nowadays, it is effortless to integrate them into an application or website.
Today’s facial recognition software achieves accuracy levels of over 99% in most scenarios. In this sense, it is essential to refer to external entities that audit the performance of these systems. In this area, the National Institute of Standards and Technology (NIST) in the United States is the highest institution in biometric standards. Companies developing these systems can submit their engines for evaluation for free, and NIST publishes the rankings publicly.