What is the principle of face recognition?

The principle of face recognition is as follows:

In fact, machines are not good at recognizing images. For example, this picture is just a string of data consisting of 0 and 1 in the eyes of the machine, and the machine can't understand the meaning of this picture. So if we want the machine to learn to recognize images, we need to write a program algorithm for it.

When we describe a person's appearance, we usually use words like melon seeds, willow eyes, garlic nose and cherry mouth. The so-called appearance, to a large extent, depends on people's head shape and facial features.

This method was adopted in the earliest face recognition. First, the machine will identify the position of the face in the image, and then draw the outline of the five senses on this face, thus obtaining the shape and position information of the five senses on the face. For example, the distance between the eyes, the connecting angle between the tip of the nose and the corner of the mouth in the horizontal direction and so on.

You can use these data to judge whether this face is a known face. Or directly find out which face this is in the database. However, the feature data obtained in this way are less and the results are not particularly accurate. Now we have more advanced algorithms to process and compare images.

For example, some algorithms no longer draw lines from images, but directly compare two images of faces, which is equivalent to obtaining more feature information in a more comprehensive and detailed way.

For example, the distance between the eyes, the connecting angle between the tip of the nose and the corner of the mouth in the horizontal direction and so on. So we can use these data to judge whether this face is a known face.

Or directly find out which face this is in the database. However, the feature data obtained in this way are less and the results are not particularly accurate. Now we have more advanced algorithms to process and compare images. For example, some algorithms no longer draw lines from images, but directly compare two images of faces, which is equivalent to obtaining more feature information in a more comprehensive and detailed way.

At present, machines even surpass humans in the accuracy of face recognition. However, with the application of face recognition technology in more and more fields, especially in the financial industry, problems have emerged. For example, criminals may use other people's photos to log in to this person's account and steal property.

One solution is to let the operator make some expressions when logging in, so that it can be judged that this is not a static photo. But even so, criminals can still simulate these facial expressions by shooting videos or modeling.

Therefore, in some occasions with high security requirements, face recognition equipment will add some special equipment to judge whether it is alive or not. For example, you can install 3D sensors, infrared cameras and other devices to sense whether the camera is shooting a cold plane image or a three-dimensional face with temperature.

Of course, face recognition technology is not perfect, criminals will always come up with new tricks to attack, and technology is constantly improving itself from this defense. Nowadays, face recognition technology has been widely used in various mobile apps and our lives. Although it is convenient for life, it also has disadvantages. I believe that in the near future, face recognition technology will be more refined and convenient.