What is Facial Recognition Technology? History, Working, & Benefits

Facial Recognition Technology

Facial Recognition Technology (FRT) is a software-based biometric identification or identity verification system that uses a digital image or video frame to identify an individual by matching and comparing distinguishable facial features.

What is Facial Recognition Technology?

Facial Recognition Technology (FRT) is a software-based biometric identification or identity verification system that uses a digital image or video frame to identify an individual by matching and comparing distinguishable facial features. To do this, FRT matches the face in the image or video frame with the faces of people available in its database. Sometimes, facial recognition technology uses both software and hardware (camera) for identification; for example, mobile and other personal devices—laptops, tablets, iPads, smartwatches, etc.—use FRT for authentication.

History of Facial Recognition Technology (FRT)

1960s

The pioneers of FRT, Woody Bledsoe, along with Helen Chan Wolf and Charles Bisson, developed a semi-automated facial recognition system in the 1960s. This system used manually marked facial features, such as the eyes, nose, and mouth, to match images stored in a computer.

They kept much of their work secret because an unnamed intelligence agency funded this project.

1970s

In the 1970s, Goldstein, Harmon, and Lest extended Bledsoe’s initial work to make it completely automated by including 21 facial features, such as lip thickness and hair color.

However, it still required manual computation of measurements and location, making it a slow and labor-intensive process. However, it was more advanced in accuracy.

1980s/90s

In 1988, Sirovich and Kirby developed a system named “Eigenface” to analyze facial features using linear algebra. This system reduces complexity and improves efficiency by identifying key features that distinguish one face from another.

Matthew Turk and Alex Pentland at MIT expanded their work in 1991 by applying Eigenfaces for real-time facial recognition. Their work was a big step toward today’s automated facial recognition systems.

2000s

In the early 2000s, NIST started Face Recognition Vendor Tests (FRVT) to evaluate facial recognition systems. Building on the FERET program, these tests helped the government and law enforcement decide how to use the technology effectively.

In 2001, the Super Bowl used facial recognition to scan for criminals, garnering global attention. While this sparked privacy concerns, it showed how useful facial recognition could be for security.

2010s – 2020s

Thanks to AI and machine learning, facial recognition technology made major advances in the 2010s. Thanks to convolutional neural networks (CNNs), computers enabled to recognize faces more correctly by analyzing vast volumes of visual data.

In 2014, Facebook’s DeepFace achieved 97% accuracy, which was comparable to human performance. Google introduced the FaceNet system, which improved face recognition in challenging circumstances such as forming images captured in low light and from different angles.

By 2017, millions of smartphone users were using face recognition thanks to Apple’s Face ID. Also, FRT became a valuable tool for public safety in cities and airports throughout the world.

The 2020s and Beyond

In the 2020s, face recognition continues to advance thanks to faster computers and stronger AI, discovering new applications in financial security and retail. Simultaneously, concerns regarding privacy and permission are gaining attention. Despite these difficulties, it is becoming an essential component of everyday technology.

How does Facial Recognition Technology work?

Facial recognition technology (FRT) software uses machine learning and artificial intelligence to distinguish an individual face from an image or video frame. It also uses statistical analysis and image processing to do this job accurately. Most commonly, people associate facial recognition with FaceID, which unlocks iPhones, but its applications extend far beyond that.

The following steps will explain how facial recognition technology (FRT) works:

  • Face Detection: The FRT software detects and isolates the face of an individual from the image or a video frame. The system tracks more detailed facial features in the image to extend the possibility of face detection. This enables the system to function effectively even in situations where there is a crowd rather than a single person, low light levels, or other challenging conditions.
  • Face Analysis: The system separates the face to analyze it deeply. Most FRT systems use 2D images, as they make it easier to match against public photos. The system then maps out key facial features like the distance between eyes, the shape of cheekbones, etc. It also determines other characteristics like age, gender, and emotions through facial expressions.
  • Converting to Data: After the analysis, the FRT system then converts the face (analog data) into digital data by marking the facial features. This converted digital data looks similar to a fingerprint and represents the person’s facial features, also known as the facial signature.
  • Finding a Match: The faceprint or facial signature is compared with faces stored in the database, like those stored personally, by law enforcement or social media platforms. If the system detects a match, it can identify the individual or display the percentage of matching in a facial recognition system.

Facial recognition is often considered one of the most natural biometric verification techniques due to its ability to recognize faces. Experts estimate that over half of the global population utilizes face recognition technology on a daily basis.

Benefits of Facial Recognition Technology

Face recognition technology is becoming an important part of many products these days. It has many benefits that make it safe and simple to use. Here are some of the major benefits:

1. Enhanced Security

Face recognition is a very safe way to log in because it uses distinctive features of the face that are hard to copy. Unlike PINs or passwords, which are easily forgotten or stolen, this technology makes sure to authorize only authentic people. Because it doesn’t use standard credentials like passcodes, it also works well to protect against phishing and other online threats.

2. Convenience

Face recognition is very popular because it is simple to use. Without having to carry keys or remember passwords, it enables users to unlock devices, approve payments, or enter secured areas. Once you become accustomed to face recognition, returning to traditional methods becomes less beneficial.

3. Speed

Tasks like signing in, confirming identification, and finishing transactions take less time because of facial recognition’s speed and smoothness. When you use a fingerprint reader, it requires physical action. But with face recognition, you don’t have to do anything. This makes it faster and easier to use.

4. Contactless Operation

Facial recognition encourages hygiene and prevents the spread of germs because it doesn’t need physical contact. In public areas or during pandemics like COVID-19, when contactless solutions are essential for health and safety, this capability is quite helpful.

5. Fraud Prevention

This method greatly reduces the likelihood of fraud and identity theft by relying on distinguishing facial features. Advanced FRT systems are able to identify small changes even between identical twins. This ensures a better degree of security and confidence by preventing fraudulent transactions or illegal access.

Takeaways

Understanding what is Face recognition technology is important, as it is a vital part of today’s digital world. Every digital product, such as smartphones, laptops, and smartwatches, incorporates face recognition technology due to its ability to make authentication safer, easier, and faster. Because it can stop fraud and allow contactless operations, it is beneficial to numerous sectors, including mobile devices, public safety, and many others. To build confidence and make sure that technology is used responsibly, it is important to find a balance between its benefits and privacy concerns.