May 4, 2020
After a long time of using, most people recognize the facial recognition technology is very convenient and useful, such as Face ID. However, this new type of technology may cause concern as now that the face has become a security method instead of fingerprints.
Like many new technologies, face detection still has shortcomings. They are increasingly evident as the military, police, or deepfake creators are trying to figure out how to make the most of this tool. More than ever, we need to understand how facial recognition technology works, the limitations, and how people will develop it in the future.
Before we dive deeper, we need to understand how facial recognition works. Here are three face recognition software applications, with a simple explanation of how it works:
Basic face recognition: For filters like Animoji or Instagram, the front camera looks for basic facial features: eyes, nose, mouth. It will then use algorithms to identify, identify facial expressions, and apply subsequent image filters.
3D recognition: Put simply, when setting up Face ID (or similar programs) on your phone, it will take a photo and measure the distance between the features on your face. Then, every time you unlock your phone, the front camera will work to measure and confirm your identity.
Identification to identify: When an organization wants to use face recognition for security, advertising, or control purposes, it will use algorithms to compare the real face with the face database collected earlier. The process is similar to Apple’s Face ID but on a larger scale. Theoretically, any database can be used (ID card, Facebook profile), but in reality, the data is usually sharp images required to capture in advance to make it easier to surface. manage.
As an Instagram user, you should know that this app’s facial recognition technology is only basic and harmless. Let’s take a closer look at the other types of recognition algorithms and the technologies behind facial recognition support:
Currently, most face recognition software uses 2D images as the main. Although 2D recognition is not entirely accurate, it makes up for convenience and low cost. Most scanners do not have the ability to collect object depth, and the photos collected in the face recognition database (such as Facebook avatars) are also in 2D.
2D images are inaccurate because they are just a flat image and lack depth identification features. With a flat image, the computer can only measure the distance between the eyes or the thickness of the mouth, but not how long your nose or forehead protrudes.
In addition, 2D recognition depends on the intensity of the surrounding light. That is, in the dark or in low light conditions, face recognition will not work. And this will be the time we need 3D recognition technology.
It is not uncommon for face recognition technology to be based on 3D images. In fact, they are closely related. This is called Lidar technology, which allows the device, for example, the iPhone, to create an infrared (IR) map on your face. The map will then be captured by the IR camera (or ToF camera) and transmitted to the phone. Meanwhile, the IR camera is responsible for measuring the time required for each bit of infrared light to travel from the face back to the phone. Naturally, the light coming out of the nasal wave will have a shorter duration than from the sides of the ear.
And after collecting facial data, the infrared camera will now use the information to reconstruct the depth map inside the device to begin the identification process. Compared to conventional 2D images, 3D depth recognition significantly increases the accuracy of face recognition software.
One of the shortcomings of 2D recognition is a reliance on lighting conditions and will not work in the dark. And this drawback can be overcome by heat sensors. With the use of an infrared sensor, face detection in the dark is now easier than ever.
Thermal cameras are capable of receiving infrared light. Specifically, warm, hot objects will emit tons of infrared rays, while cold objects only emit a negligible amount. Even expensive thermal cameras are capable of detecting temperature differences on the same surface, so it’s an ideal technology to apply to facial recognition.
Here are some different ways to identify faces with a heat sensor. All techniques are complex, but they generally have some basic similarities, including:
Need more images: A thermal camera needs to take multiple pictures of an object. And each image focuses on a different spectrum of infrared light (long waves, short waves, and mid waves). Usually, the longwave spectrum provides the most detail of the face.
Vascular map: These infrared images can also be used to extract the process of forming blood vessels in a person’s face. While scary, the vascular map can be used as a fingerprint. They can also be used to measure the distance between facial organs (if the image is poor quality) or to identify bruises and scars.
Identify the object: A composite image (or dataset) created with multiple infrared images. This composite image can then be compared with the face database to identify specific subjects.
Of course, thermal face recognition will only be used in the military and will not appear on phones in the future. In addition, the heat sensor does not work well during the day (or in good light) so it does not have much potential for use outside the military.
View our case study for facial recognition technology: https://inapps.net/face-detection-application/
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