With the rapid development of technology, the use of facial recognition is becoming increasingly widespread. This article will provide you with the top 5 most common facial recognition applications and the latest insights.
AI face recognition is a biometric technology that uses AI to identify facial vectors and features and then compares them with those stored in a database, for the purpose of verifying identity. While our 2025 Ultimate Guide to Facial Recognition provides a complete and comprehensive overview of facial recognition technology and how it works, this article will focus on facial recognition’s functions and application areas.
The 5 most common use cases for facial recognition today are:
In recent years, security and surveillance has become the most popular application for facial recognition. According to the latest data in 2023, access control and security control applications will account for more than one-third of the global face recognition market revenue in 2025, and are expected to continue to maintain the leading position in market applications by 2032.
Security and surveillance systems are an important tool in the protection of property and personal safety. However, whether it is through home cameras, CCTV (closed caption TV) systems, or video surveillance systems, they all traditionally rely on long-term manual monitoring and manual alerts of unexpected events. This process is cumbersome, expensive, and unreliable.
Integrating AI face recognition in security systems to accurately determine the identity of people entering and exiting, search for specific people in images, and automatically report when human intervention is needed, can significantly improve the accuracy and convenience of monitoring. Additionally, integration reduces the risk of human error and cuts the cost of manual monitoring.
AI face recognition operates by matching real-time images against a database of pre-enrolled identities, enabling better monitoring of protected premises and alerting key personnel if an unidentified or banned individual enters. For example, consider offices and schools. Facial recognition enabled security systems can help authorities monitor the flow of people and alert the proper authorities for immediate action when a known criminal or unidentified subject approaches or enters the facility. Currently, corporate security and internationally renowned department stores have introduced CyberLink face recognition technology, FaceMe® Security, to detect the entry and exit of block-listed individuals and provide immediate alarms, effectively improving site security and reducing industry losses.
In large spaces such as transit stations, shopping malls, amusement parks, and exhibition centers, locating a specific person normally requires security teams to manually view a large number of surveillance images. With AI face recognition, the process is expedited. For example, an 87-acre Fairgrounds and Exhibition Center in the United States has adopted FaceMe® Security and People Tracker facial recognition technology to enhance the safety and security of visitors.
Traditional access control and time and attendance management systems require employees to use physical identification (e.g., badges), personal information (e.g., pin codes), and even biometrics (e.g., fingerprints) to clock in and out or access restricted areas. However, the first two methods have an increased risk of impersonation and buddy punching, as employees can accidentally lose badges or share pin codes. Fingerprinting is accurate and non-transferable, but it also unnecessarily increases the number of contact points and, consequently, the possibility of germ transmission.
When utilized for access control and time and attendance management, AI face recognition is convenient and eliminates the risk of lost or stolen credentials and germ transmission. Customers who have deployed CyberLink face recognition technology, FaceMe® SDK and FaceMe® Security, for access control and time and attendance management can generally be divided into the following three use cases.
Facial recognition combined with physical access control devices is the most common use case. Widely used in commercial and residential facilities to grant access to authorized employees, family members, or pre-registered guests – or restrict access to unauthorized persons, facial recognition provides convenience and security. Examples include:
Unlike access control devices that only allow one person to pass through at a time, IP Cameras can accurately, and simultaneously, identify multiple people as they enter or exit. This is more efficient for businesses with a large number of employees and a large flow of people, such as:
By implementing facial recognition functionality within an APP, the technology can more freely be combined with various edge devices, such as mobile phones, tablets, and self-service kiosks. Examples include:
Similar to facility or building access control, certain equipment or specific services may only be used by authenticated individuals. Depending on the use case, authentication must sometimes take into consideration the use and detection of personal protective gear or safety equipment. Examples include:
Within the auto manufacturing industry, quality control systems can only be operated by qualified inspectors. To provide inspectors wearing facial masks and safety googles with a touchless and frictionless identity verification method, Toyota Japan integrated FaceMe® SDK for its ability to accurately authenticate individuals, even when their face is partially obstructed.
Simpello, an American provider of smart hotel applications, has streamlined the hotel check in experience by integrating facial recognition into the process. When booking a room through an online booking app dedicated to hotel chains (such as Marriott and other international chains), travelers can choose to save their facial features for subsequent comparison. Upon arrival at the hotel, they can then use AI face recognition at the hotel’s self-service check-in kiosk to verify their identity and receive their room key. Not only is it convenient to use, it can prevent others from registering under their names, and also allows hotel staff to focus on guest experiences other than check-in.
Know Your Customer (KYC) is a regulated global practice in financial services. It requires financial institutions to verify the identity, suitability, and risk factors associated with their business relationships, including their clients.
The first step in the KYC process is to verify the customer's identity, usually through manual confirmation of an individual’s government issued ID. This step normally requires a customer to physically visit their financial institution; however, when facial recognition is incorporated, traditional, in-person, verification can be eliminated, transforming the KYC process to electronic Know Your Customer (eKYC). As an eKYC authentication method, facial recognition matches a live face capture to an ID that has already been scanned or is on file, confirming the person’s identity before granting access to services and products.
In addition to eKYC, facial recognition can be used for identity verification in all aspects of online account opening, remote insurance purchases, account deposits and withdrawals, online transactions, and cryptocurrency transactions. Note, the actual scope and related restrictions vary depending on the laws and regulations of each country.
Examples of financial institutions currently introducing AI face recognition in order to implement eKYC include:
As organizations begin to place greater emphasis on cyber security and the protection of their digital assets, many are turning to multifactor authentication (MFA) and anti-spoofing practices to secure their data.
2FA methods typically consist of a combination of passwords, one-time passwords (OTP), hardware (IC cards, USB devices), biometrics (face, fingerprints, iris), etc. Among those verification methods, passwords are easy to forget, one-time passwords cannot be used offline, and hardware is prone to theft.
Among biometrics, facial recognition is the most accurate and convenient to use, which is why government agencies in Japan integrated CyberLink face recognition technology, FaceMe® SDK. Required by current regulations, civil servants, especially those in the IT department must use two-factor authentication (2FA) if they want to log in to official computers and access information related to the public identity card number.
Liveness detection can be used to further strengthen 2FA when using facial recognition as a factor. To ensure a live person is in front of the camera, a 3D depth camera or infrared camera may be used, or users may be required to take specific actions while in front of the camera. For example, South Korea’s UNION COMMUNITY Ubio-ezPass identity verification solution requires users to enter a password and successfully pass face recognition with liveness detection to log into corporate computers. This prevents malicious attempts to hack the face recognition system with photos or videos.
To learn more about liveness detection and anti-spoofing, read:
When designing a face recognition solution tailored to your specific needs, it is helpful to evaluate similar, well accepted, and widely deployed use cases. For example, if you want to implement AI face recognition for employee and visitor access control, you can learn from existing deployments in businesses with comparable sizes and scope. This article provided real applications; however, there are countless uses for face recognition, such as smart retail, robotics, manufacturing and many others. You can read more CyberLink FaceMe use cases here.
After you’ve determined your unique usage scenario, our 7 Success Factors for Choosing the Best Facial Recognition Solution article can help you select the best face recognition system based on your accuracy, performance, software, and hardware architecture needs. Have questions? Contact us and a member of our team will be happy to assist you.
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