Use Cases

Facial Recognition: Top Use Cases

In this article, we examined what face recognition is, how it works, the top use cases of face recognition, and the challenges of facial recognition.
Alan Kilich
3 minutes

In a short time, facial recognition has gone from being a technological curiosity to becoming an essential component of our everyday lives. The technologies used for facial recognition are making rapid strides forward, and the algorithms used by these technologies are becoming more and more powerful. Their applications are incredibly diverse and countless.

Before explaining the top use cases of face recognition, let's first look at what face recognition is and how it works.

What is Face Recognition?

The process of recognizing human faces based on their unique biometric characteristics or using a person's facial characteristics to verify them is known as facial recognition. The technology is used for various purposes, including logging a user into their phone, passing through a door, or searching for a specific person in a database of pictures.

This form of identification is also effective for various commercial and law enforcement applications. Face recognition software is a beneficial instrument for catching criminals in the act, protecting the public from danger, identifying people who cannot identify themselves, and identifying the deceased, as well as enhancing security and personal protection.

How Does Facial Recognition Work?

Face recognition systems use computer algorithms to recognize facial traits. These characteristics, such as eye distance or chin shape, are mathematically encoded and compared to a face recognition database.

Data on a specific face is often known as a face template, and it is separate from a photograph because it includes only those details that can be used to identify one face from another.

For the software to recognize people's faces, it needs to be able to distinguish between a basic face and the rest of the background. The ability to identify a face and then scrutinize it into its component parts is the basis upon which facial recognition software is built.

Every single face has a variety of distinct landmarks, which are the various hills and valleys that make up the different facial features. After measuring these landmarks, a numerical depiction of the person's face, known as a faceprint, is formed and stored in the database.

Face prints are compared to a database of other known faceprints to see if one matches the other. If the unique face print matches a known one in the database, then the match is correct.

Where is Facial Recognition Used?

As the use of face recognition technology grows in popularity, it's no surprise that plenty of sectors are seeing it as a potential tool. Facial recognition software has a variety of applications, ranging from law enforcement to airport security to phones and other personal electronics. Among the various uses for face recognition technology, these are the top use cases.

Law Enforcement

The use of facial recognition in law enforcement is on the rise. Various databases are used by law enforcement authorities to identify and verify people of interest.

Factories

Since face recognition is the quickest biometric identification technique available and needs minimum user engagement, it can help to quicken access control in factories.

Health Care

Facial recognition can help with the accurate identification of patients, thereby reducing the risk of mistakes during treatments and misdiagnosis.

Business

Time-and-attendance activities are time and money-consuming. When a business uses a manual time and attendance system, there are many administrative responsibilities to accomplish. A completely automated system with face recognition provides a single place to organize and execute these procedures.

This was a brief overview of face recognition technologies for various contexts. Let's dive deep into the top use cases of facial recognition.

Key Use Cases of Face Recognition in Law Enforcement


Face recognition is increasingly being used in everyday policing by law enforcement authorities. Arrestees' mugshots are matched to municipal, state, and federal databases. When an arrestee's photo is taken, it's saved in a database and examined throughout every criminal inquiry.

Law enforcement agencies may then search these large mugshot databases to identify people in images collected from social media, CCTV, traffic cameras, or even photos they've taken themselves in the field. Faces may also be matched in real-time against hot lists of people suspected of illicit activities.

Officers can utilize smartphones, tablets, or other portable devices to snap a picture of a motorist or pedestrian in the field and quickly compare that photo to one or more facial recognition databases to try identification.

In addition, police enforcement has utilized face recognition to identify people who may be sought in connection with crimes at huge events such as concerts, sports events, and the Olympics.

How Factories Can Use Facial Recognition for Access Control Systems

Face recognition technology is an effective solution for factories that want to adopt the most current, reliable, and quick technology while simultaneously improving the user experience in access control applications.

Every day, factories, warehouses, and labs are frequented by hundreds of people, including workers, visitors, suppliers, and technical staff from outside the organization. The data of the business has to be protected at all costs, which requires more stringent entrance and exit processes. It is necessary for businesses to keep detailed records of employees' time on the job, as well as their attendance and their levels of access.

This is where face recognition comes into play. Facial recognition software placed on workstations can recognize numerous visitors at once and quickly and precisely record their admission and exit. Facial recognition technology can also limit who can operate certain components of machinery and equipment.

Additionally, by combining face recognition software with streaming media management systems (VMS) and real-time messaging systems, businesses can increase the overall effectiveness of human oversight. By eliminating the need for security staff to manually navigate many displays, automated procedures are optimized, and operations management is made more effective.


Healthcare: quicker processes and safer procedures with facial authentication

There has never been a time in the history of healthcare when a lack of qualified workers, a tremendous workload, and wage discrepancies are more apparent. It's reasonable to state that if doctors and nurses ignore their own health, they won't be able to provide their patients with the best treatment possible. Businesses, healthcare advisers, and employees have high expectations for the integration of technology into healthcare, given the current situation. Technology has the power to improve patient diagnosis and treatment while reducing the strain on healthcare professionals.

Security identification methods abound, including passwords, two-factor authentication, fingerprint recognition, and others. However, none of them are as effective as facial recognition. Mathematical patterns are the foundation of this technology, and they maintain the data's security.

Face Recognition is powered by Artificial Intelligence (AI). It can be used in many ways in the healthcare industry, such as patient check-in and check-out procedures, diagnosing diseases and conditions of patients, and emotion detection for mental therapy.

For example, a "health mirror" measures critical body signs using light. A computer or camera can replace the mirror. Telemedicine is bringing treatment closer to our homes, and we're nearly there. Face scanning health applications can tell you your health state. Looking at the camera can monitor heart rate, blood pressure, tension, and more. This is where facial recognition can provide remote diagnoses to people.


The healthcare sector is seeing upheaval due to facial recognition technologies. Face recognition has impacted everything from computer-aided diagnostics to emotion detection in mental treatment to securing sensitive data and more. Facial recognition is, without a doubt, a revolution in healthcare too.

Business: Facial Recognition Helps Companies Save Time and Money


In today's world, facial recognition in the workplace will become more and more common. Business owners all over the world are seeking contactless solutions for payroll calculation and employee clock-in/out. Biometric time and attendance solutions will therefore be used more often than they were in the past.

However, for some people, facial recognition technology might evoke unpleasant feelings. However, facial recognition can be very helpful when carried out safely and in accordance with biometric time clock legislation.

It helps to organize and carry out some activities such as attendance control, work performance overview, and security control in one simple, a central place with the help of a fully automated time and attendance system with face recognition.

It gives business owners more time on their hands to work on more urgent and important activities. As a consequence, they will be able to concentrate on what's crucial—growing the business.

Digital Media: How Face Recognition Helps?


As in other industries, it is possible to get help from face recognition in other fields such as digital media.

For example, applications use face recognition to detect faces in videos. Thus, the target face can be processed without watching the whole video and without the need to edit the whole scene. It is also possible to use face recognition in live broadcasts. Broadcasters, news agencies, and producers can identify faces with face recognition and perform some operations like effects.

Also, phone apps in the digital world benefit from face recognition. Applications that create simulations that suggest the outfit you will wear or suggest a hairstyle at the hairdresser benefit from face recognition.

In short, the usage area of ​​facial recognition is quite wide, and it appears in many areas, making our lives easier.

The Challenges of Facial Recognition in the Work Environment

There has been a recent uptick in the use of facial recognition technology in the field of security, especially in large-scale settings such as factories and plants. It is necessary to triumph over the following obstacles in order to effectively incorporate AI face recognition technologies into large-scale work environments:
Poor Lightning & Angles

Personnel and vehicles continually enter and depart vast venues; therefore, smart access control systems require indoor and outdoor face recognition cameras.

Outdoors, faces are backlit during the day and excessively dark at night. Outdoor lighting can impair face recognition technologies.
Also, sometimes camera angles can make facial recognition harder. Due to the angle sensitivity of the lenses, low light, and the camera's own angle, the half image will damage the Facial Recognition performance.

Fortunately, it is possible to solve these problems with advanced AI-based services such as Cameralyze. Thanks to AI, with features such as sharper imaging, night vision, and positional viewing, processes are done even in moving objects in daylight or night light. Thus, operations are not interrupted.

Crowded Areas

Hundreds of thousands of contractors, temporary construction workers, and foreign technical specialists pass through huge companies every day. During peak hours, factories require face recognition, access control, and check-in.

Advanced services such as Cameralyze can easily solve these problems thanks to their powerful software editing and can identify hundreds of faces in a frame.

Partially Covered Faces

Some factory workers must also follow the usual safety protocols when operating equipment. They should wear face masks, safety helmets or hats, and safety glasses all day. Therefore, their faces are more difficult to recognize. During rush hours, many employees switch equipment on and off, which reduces productivity, wastes time, and increases costs.

Advanced face recognition systems use deep learning to match veiled faces with personnel databases. Thanks to AI-based deep learning, faces can be identified with up to 99 percent accuracy. Thus, both time and performance are saved.

Final Thoughts

To sum things up, we can clearly see that facial recognition technology is transforming the society we live in, and it seems like we are just scratching the surface when it comes to the possible uses of facial recognition software. A large number of companies may benefit from face recognition technology since it speeds up and improves identification procedures. By verifying that people are who they claim to be, it increases both public and individual safety.


Cameralyze offers an innovative facial recognition solution that is designed for the security controls of smart manufacturing. Large-scale settings can improve both the security of their access control systems and their general efficiency with the help of face recognition technology. This is accomplished through real-time face matching and masking, as well as the integration of third-party systems and other value-added activities.

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