Using artificial intelligence to track and recognize faces was once the reserve of science fiction. However, this technology has become so widespread that 60 percent of countries now use face detection and recognition in their airports.
It is also common in the smartphone in your pocket, and many industries use it for identification and verification. Facial recognition software is also proving a valuable security tool at large events and crowded places.
You may think that face detection and face recognition are the same. The two are linked, but there are significant differences in how they operate.
It is vital to use the correct terminology as each technology uses specific software and has different real-world applications. If you work in the security industry or law enforcement, you need to know which technology is relevant and when to use it.
This article will take a deep dive into the differences between face detection and facial recognition.
Face detection is the first step on the path to facial recognition.
This technology can look at a frame, image, or video and tell if a human face is present. In this case, it does not matter to whom the face belongs.
Face detection software can sift through a variety of other items, such as trees, buildings, tables, or a lamp, and pick out the faces. It can also count the number of human faces detected. The software can do this no matter what pose a person is standing in, what they are wearing, or the state of the lighting.
There are various methods used to train a computer to detect faces. The algorithm needs to learn what a face is and how to distinguish it from other items.
One way to do this is using the technique humans use. We know that a face has eyes, a nose, and a mouth and where they are situated. Using this set of rules, a computer will learn to seek out these features to identify a face.
The easiest method is to start by looking for eyes. If the software picks up on one of these identifying characteristics, it will move on to the following features.
This knowledge-based method may run into problems when it comes to different skin colors and lighting conditions.
Using deep learning artificial intelligence techniques, the computer receives a large set of data -- in this case, photographs -- to learn the difference between a face and other objects.
Other methods may use face templates that the software will use to compare against the objects it is scanning or compare specific features such as skin colors. A face is rarely still, which allows some software to detect its motion, especially in a live video.
Often a combination of these techniques is used to eliminate errors. Experts highlight the importance of using a diversity of images to train computers. Different races, or non-binary genders, often trip up face detection software.
One of the most common applications of face detection these days is on your smartphone camera. The block that forms around a face is your camera detecting its features and using this information to auto-focus.
Have you ever walked past a temperature scanner in an airport or shopping mall that suddenly knew it was time to measure whether you have a fever or not? These machines became widespread during the Covid-19 pandemic.
They are able to detect the presence of a human being using face detection technology.
Face detection has also become popular, along with other forms of object detection, in the field of security. You can use it at home to receive an alert when someone is at your door. Managers of a busy store can use it to keep track of how many customers they have. Security officers and event organizers can track how many people are entering a football stadium or concert.
Another interesting use of facial detection is to create realistic facial expressions and movements in animated movies or computer games. Popular filters on Snapchat, TikTok, or Instagram start with face detection.
Face detection is crucial to the more complex task of facial recognition.
The facial recognition market will grow from $3.83 billion in 2020 to $16.7 billion in 2030. The technology has become so accurate there is only a 0.8 percent error rate. Less than eight years ago, there was an error rate of 4.1 percent.
So what is facial recognition?
Facial recognition technology will start with the process of face detection. It will scan a photo or video and pick out the human faces. However, it will then take the process a step further.
The software will compare the biometric image of the face it has scanned with previous images it has seen. This can be a limited set of faces that are allowed access to a specific building. But, it can also be a massive database of images it has recorded over time.
Using this data, it will try to make a match.
While face detection trains a computer to pick out a human face, face recognition software will analyze the image.
It will turn the image into a set of data about your facial features. This can include the distance between your eyes, forehead, and chin, and other geometric measurements. There are dozens of different factors that the software will measure.
It will then analyze its database and look for an exact match, comparing the data it has gathered.
While this technology is highly accurate, it will rarely pass the facial recognition test of differentiating between identical twins. This is only possible in very high-quality images where software can pick up differences such as a freckle or tattoo.
The first large-scale use of facial recognition came in 2001 when police used the technology to scan a massive crowd at the Super Bowl in the United States. Many were shocked by such a futuristic idea.
However, it has now become commonplace.
One use of facial recognition technology is verification. For example, a facial recognition app that allows your smartphone to scan your face and grant you access to your device. It detects your face and compares it to the image it stored when you set up your biometric security.
Verification using face recognition is used on banking applications or when boarding an airplane. It can make passing through an airport or any other place requiring identification a smooth and more pleasant experience.
Security is one of the most important applications of facial recognition technology.
Intelligent video analytics allows security professionals to scan crowds and pick up threats. This includes recognizing known criminals or seeking out unfamiliar faces. Some casinos may use this technology to spot troublesome gamblers.
It is also useful if you are looking for a missing person, such as a child who has gotten lost in a crowded area.
When facial recognition goes a step further, the software can analyze the gender, age, and emotions of the person it is studying. This has even broader applications, such as allowing stores to gather details on their customers.
There are many common places where the average person has run into facial recognition. These are mainly online. When Facebook asks you if you want to tag a specific friend or if you indeed appear in a particular picture, it uses the technology to scan millions of images in its database and match them up.
Google also uses the technology, which allows it to organize photos in Google Photos or reverse search pictures to find similar images. Many news organizations use this to fact-check viral videos and photos that are being misrepresented.
Facial recognition technology is only one aspect of AI-powered video analytics. This technology will allow you to monitor multiple security movements, prevent accidents and detect threats before they become a problem.
It also simplifies the task of combing through hours of video for evidence in the aftermath of a crime.
While there are key differences between face detection and recognition, the two also work hand-in-hand. Facial recognition technology would not be possible without the ability of software to pick out a face from among various other objects.
Two-i Video Analytics software uses a wide range of object detection software, including facial recognition. It sends instant alerts when a threat is detected and allows you to cut down on the time you need to review CCTV footage when there has been a security incident.
Contact us for a demonstration of our video analytics solution.