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How Face Recognition Technology Shapes the Future across Multiple Industries

  • 作者:HFSecurity
  • 发布时间::2020-12-08

In the past ten years, facial recognition technology has been a good choice. Although it has existed since the 1960s, any large-scale attempts to successfully implement it have failed. The main reason is its lack of precision and scalability. Everything changed in the late 2000s.

In 2011, the Pinhelas County Sheriff’s Office and Panama’s Tocumen Airport both implemented their own facial recognition systems and achieved impressive results. Drug smuggling and organized crime activities in Panama have been greatly reduced, and the time for the Pinhelas County Sheriff’s Office to conduct criminal investigations has been greatly reduced.

Next comes mainstream applications.

Facebook introduced a facial recognition feature that reminds you when you upload unmarked photos and videos in 2012. Google took full advantage of the company's rich experience in AI and machine learning to produce Google Photos in 2015. Last year, Apple was on iPhoneX.

What is facial recognition technology? Why is it the "next big thing" in the tech world?

What is face recognition
Face recognition technology has one goal: to recognize faces. Among all biometric systems available, it is the least invasive and fastest technology.

The facial recognition system does not require people to scan fingerprints, hands or iris, and can easily take pictures of people's faces. In most cases, the subject does not even know the process. This eliminates the feeling of being monitored or invading privacy.

Due to the use of neural network algorithms, facial recognition systems are also very effective in generating results.

Our brain subconsciously recognizes the different features of the face-the space between the eyes, the height of the hairline, the width of the nose. Facial recognition algorithms need to do this consciously.

The neural network uses the human brain as a model, so it tries to imitate the process of recognizing faces. The Massachusetts Institute of Technology best explains how neural networks are constructed:

"Neural networks are composed of thousands or even millions of simple processing nodes connected to each other. Most of them are organized into layers, and they are "feedforward", which means that data only passes in one direction. They. A single node may be connected to multiple nodes in the next layer (receiving data from that node), and several nodes in the upper layer (sending data to it).

Facial Recognition Device
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The node will assign a number to each of its incoming connections, called a "weight". When the network is active, the node receives a different data item (a different number) on each of its connections and multiplies it by the associated weight. Then add the resulting products together to get a number. "

Do you know how to transform into a facial recognition system?

Once we use a 2D or 3D camera to capture our facial information, the neural algorithm will then analyze and create a unique digital template based on the facial information. This digital template is like a human brain, and neural network algorithms can be used To measure the distance between two eyes, such as something shaped like a nose, this algorithm can be accurate to 1 micron to "remember" our appearance

Fare recognition technology
Face recognition technology can also resolve differences that may change our appearance. We can find some examples, these examples are some facial hair, the color of the hair, and the angle at which the picture was taken.
Once the template is created and stored, it can be used for multiple purposes: detection, verification or identification.

The difference between face detection, face verification and face recognition.
Facial recognition technology can be applied in some areas. These areas are often chaotic.
HFSecurity Face Recognition Device

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Face Detection
The face detection method is bound to be a more extensive and simple professional term for face recognition. Face detection is related to identifying whether a human face exists in an image or video, rather than a person.

There are many applications for face detection. The camera's automatic function uses face detection to determine the most important part of the photo. Face detection can also be used to count the number of people entering a specific area. Self-driving cars also use it to determine if someone is crossing the road.

Snapchat's filters are a trivial use of face detection that you may have experienced. The filter looks for the presence of human faces, and then maps facial landmarks (eyes, nose, lips, etc.) to know where to place them, such as flower crowns or cat ears.

Face verification

Face verification (also commonly referred to as face authentication) is about verifying identity based on facial images by checking existing databases.

Facial authentication involves only comparing an input image with an image belonging to the person's claimed identity. In other words, the system will only compare your face with a picture, not the entire database.

Face recognition

Face recognition (also called recognition) involves comparing an input image with all the images in an image library to determine who the input image belongs to. Or if Or in other words, this is not within the authority of the database

An example of a facial recognition system is to submit a photo of a criminal suspect to a police database for matching, such as that done at Tocumen Airport in Panama.

Application of face recognition technology in real life
Face recognition technology has been used in many industries, from the passage of time to national security issues.


In the past few years, some hospitals have begun to use facial recognition systems to simplify patient handling. The system matches appropriate patients with their records, thereby preventing duplication of records or record supervision.

HFSecurity Face Recognition Device

In case of emergency, we can use the function of another direction area of the face

Whether at the scene of the accident or during transport to the hospital, patients are usually unable to communicate or respond slowly, which makes it difficult to obtain medical information that is essential for medical care. Facial recognition provides a quick way to access medical information, and in many cases, can speed up the process of providing necessary medical care.

Facial recognition can also help screen for certain diseases. For example, researchers at Duke University have developed the Autism & Beyond app, which uses the iPhone’s front camera and facial recognition algorithms to screen children for autism.


In the use of facial recognition, the security department is a senior person.

Since the introduction of digital biometric passports in 2006, facial recognition has been used in many countries/regions.

As mentioned earlier, the police force is also an avid user of facial recognition technology. The most memorable achievement of this technology was in 2016, when the FBI facial recognition software was used to identify the "hat man" responsible for the Brussels terrorist attack.

Many high-security facilities, such as government buildings and nuclear power plants, use facial verification technology to check the identities of employees.

Retail, marketing and advertising

Facial recognition is still in its infancy in retail and marketing, but big companies have some interesting attempts.

One way to use facial recognition technology is to place the camera in a retail store. In this way, the customer's buying process can be analyzed and improved by accessing customer information from the customer's social media profile and providing customized offers and products.

The American department store Saks Fifth Avenue is already using this system. It is reported that Amazon GO stores are also using it.


The banking industry is using facial recognition to prevent fraud and make online banking more secure. HSBC has launched a Face ID verification option for corporate customers in more than 24 countries/regions. Face ID registration is faster than touch ID.

in conclusion
Face recognition is an emerging technology that can bring many benefits. For companies that implement facial recognition correctly, resources and time can be saved, and even new sources of revenue can be generated.

What is the future of this technology?

It is difficult to determine. Some experts predict that our faces will replace ID, passport and credit card passwords. Considering the convenience and cost-effectiveness of the technology, this prediction is not far away.

If this prediction becomes a reality, any company that implements the technology today could gain a competitive advantage in the future.

Related News:

Facial Recognition Is Everywhere. Here’s What We Can Do About It

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The future development of face recognition will break through the scope of security applications

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