What is the main research direction of face recognition?

Large-scale face search based on big data is an important direction for the future development of face recognition technology. For example, in the field of public security, it has entered the era of big data, and some traditional technical bottlenecks have emerged, so the use of face recognition technology to make use of these massive data and improve the management level of the entire public security informatization is an important direction for the development of face recognition technology in the future.

With the acceleration of China's urbanization process, problems such as social stability and urban security have gradually emerged, and face recognition technology is the key technology to achieve a safe and secure city. Therefore, with the large-scale construction of smart cities, the application of face recognition technology will be a new trend in the future.

With the development of 3D measurement technology, the 3D face recognition algorithm can make up for the problem of loss of effective recognition information caused by 2D projection, and has a good solution to the traditional difficulties of face rotation, occlusion and extreme similarity, and has gradually become another important development route of face recognition technology.

Mostly used for payments. It's quick and easy, and you don't need to enter a password. But for now, Apple's 3D face recognition is the most secure.

The disadvantage is that the posture is not right and cannot be recognized. Samsung's face recognition is very embarrassing, the light can't be recognized, the angle is too biased to recognize, and the requirements are more demanding. Apple's is fine.

That's about it. As for the application, it's still based on the phone itself.

Deep learning has improved the accuracy of face recognition to the naked eye, greatly expanded the application scenarios of 2D face recognition, and with the help of the outbreak of Internet finance, it has entered the financial-level application and rapidly popularized as infrastructure. In addition, with the explosion of demand for identity authentication in Internet finance and other businesses, third-party authentication service platforms will emerge, and there is huge room for development of platform-based profit models based on service provision.

The rapid development of the security industry has provided a stage for face recognition applications; On the other hand, with the further development of face recognition technology, it has opened up a new market for the security industry. The analysis believes that intelligent analysis will be one of the future directions of the security market, and face recognition is one of the very important technologies and applications.

3D image processing chip manufacturers: STMicroelectronics, Texas Instruments, Infineon, Primesense, TX transmitter component manufacturers: VCSEL part of Finsar, Lumentum, Princeton (acquired by AMS), Accelink, Huaxin Semiconductor, Zonghui Optoelectronics, DOE part of Qijing Optoelectronics, Germany CDA, France Silios, Germany Holieye, TSMC, precision materials, WLO part of AMS, Huatian Technology (post-processing).

It only takes 4 steps to understand how the face recognition module works

Before we dive into edge face recognition and its applications, let's first explore how the face recognition module works.

Facial recognition technology can identify or verify an individual's identity by analyzing their face. Facial recognition AI operates by matching the faces captured by the camera with a database of pre-recorded faces.

Although there are many types of facial recognition systems, they usually work in the following ways:

Step 1: Face Detection recognizes faces.

The camera locates and recognizes clear images of faces. Faces can be recognized when individuals are individually or in a group.

In addition, face detection can identify people on the front or side, so the camera can only capture their personal data.

Step 2: Face analysis measures the face.

Analyze the image by reading how the face is mapped.

Artificial intelligence software analyzes and measures things like the distance from the forehead to the chin and the distance between the eyes. It also determines the shape of the ears, lips, jaw, and cheekbones, among other things. The aim is to identify the key features of your face that make you who you are.

Step 3: Convert the captured images into data.

Based on all the measurements collected, the faces classified as analog information are converted into data and classified as digital information. The face is now converted into a mathematical formula that has its own number ** called the face pattern. Facial fingerprints are like fingerprints. No two are the same.

Step 4: Face matching compares your face to a database.

An individual's faceprint is now in the database and can be compared with all other faceprints. A person is assigned an identity when their face print matches another image in the face recognition database.

The traditional face recognition technology is mainly based on face recognition of visible light images, which is also a familiar recognition method and has a history of research and development for more than 30 years. However, this method has insurmountable drawbacks, especially when the ambient lighting changes, the recognition effect will drop sharply, and it cannot meet the needs of the actual system. Solutions to solve the lighting problem include 3D image face recognition and thermal image face recognition.

However, these two technologies are far from mature, and the recognition effect is not satisfactory.

One solution that is rapidly developing is multi-source facial recognition technology based on active near-infrared images. It can overcome the effects of light changes and has achieved excellent recognition performance, surpassing 3D image face recognition in terms of overall system performance in terms of accuracy, stability, and speed. This technology has developed rapidly in the past two or three years, making face recognition technology gradually become practical.

Face recognition technology refers to the use of computer technology for analysis and comparison to identify faces. Face recognition is a popular field of computer technology research, including face tracking detection, automatic adjustment of image magnification, night infrared detection, automatic adjustment of ** intensity and other technologies.

Face recognition refers to technology that is able to identify or verify the identity of the subject in an image or **. The first facial recognition algorithms were born in the early seventies [1,2]. Since then, their accuracy has improved dramatically, and people now tend to prefer facial recognition over biometric methods traditionally considered more robust, such as fingerprint or iris recognition[3].

One of the big differences that makes facial recognition more popular than other biometric methods is that facial recognition is inherently non-invasive. For example, fingerprint recognition requires the user to press their finger to the sensor, iris recognition requires the user to be very close to the camera, and voice recognition requires the user to speak loudly.

Comparatively, modern facial recognition systems only require the user to be in the camera's field of view (assuming they are also reasonably far from the camera). This makes facial recognition the most user-friendly biometric method.

This also means that the potential applications for facial recognition are wider, as it can also be deployed in environments where users do not expect to work with the system, such as surveillance systems. Other common applications for facial recognition include access control, fraud detection, authentication, and social**.

In recent years, with the rapid development of artificial intelligence technology, AI face and voice technology has been known by more and more people. Although there are many potential applications for this technology, it also has some potential threats, especially in the financial sector. Many people are already suffering financial losses as a result, so it's important to understand these threats and how to better protect against them in our daily lives.

One. What is AI face swap and voice swap technology.

AI face-swapping and voice-swapping technologies are two relatively emerging technologies that can transform one person's face or voice into another's. This technology can be well used in film and television production, production, etc., and can also be used to achieve more realistic **** or online live broadcast.

Hackers, on the other hand, can use this technology to carry out scams and fraudulent activities. Thanks to the popularity of AI technology, hackers can now use face and voice swaps to make very realistic ** and audio, and use it to deceive, such as fake banks**, **departments**, or fake the content of important people's speeches through social **, etc. These threats can directly lead to the damage to a person's financial and credit history.

Two. How to prevent it.

While this technology may seem scary, there are a few things we can do to prevent ourselves from becoming victims.

1.Protect personal information and enforce password difficulty.

Hackers often use personal information to carry out scams and deceptive activities, so we should always protect our personal information. Especially on social media, we should avoid posting our profile and location information. We also need to pay more attention to the difficulty and accuracy of passwords, and protect ourselves with more complex and harder to guess passwords.

2.Establish two-factor authentication.

To prevent hacking, we should enable two-factor authentication options for our banking, social, and communication, among others. In this way, even if the password is stolen by hackers, it is difficult to steal information such as mobile phone verification codes.

When answering unfamiliar unknowns, you should consult the relevant departments or agencies to find out if these ** are really from the authorities. When accepting the ** confirmation, it is also necessary to confirm the ** of both parties in response to ensure the authenticity of the ****.

4.Be wary of misinformation.

When we receive unreasonable or untrue information, we should be more careful and cautious. This includes information that threatens our personal information, money, and security.

Overall, we need to strengthen our own awareness of the fight against hackers, and build and continuously update our awareness of data protection and security. As of now, it seems that the face-swapping technology in AI is still difficult to be used by hackers, but it is still necessary to remain vigilant and implement more cybersecurity measures.