Introduction to facial recognition technology
Facial recognition technology is a field of computer vision that allows you to identify or confirm the identity of a person by their face. It has come a long way since its inception. It was initially used for simple tasks such as finding matches in photographs. In the 1990s, scientists began to develop more complex algorithms for real-time facial recognition.
Today, this technology is actively used in various fields such as security (e.g. airports), mobile devices (phone unlocking), the financial sector (to protect accounts and transactions), and in retail to improve personalised services.
Modern facial recognition technologies use machine learning and artificial intelligence techniques that are trained on huge datasets, making them more accurate and faster. Such technologies can operate in real-time environments with high accuracy and minimal errors.
Market Statistics
The global market for biometric technology continues to grow. The facial recognition market is projected to grow to $ 99.63 billion in the coming years, which is a significant increase from $ 33.26 billion in 2019. This confirms the widespread interest in utilising this technology for various needs.
The significant growth in the market is attributed to the high accuracy of facial recognition, which has reached a level of 99.97% under ideal conditions, coupled with decreasing hardware costs and improved software solutions. Facial recognition has also become available for mass applications such as smartphones, which has fuelled its adoption among common users.
With increasing applications and improved technology, facial recognition is not only becoming more affordable but also more effective, opening up new prospects for adoption in areas ranging from security to personalised marketing solutions.
Applications of facial recognition in different industries
Facial recognition technology is now being used extensively in a wide variety of industries, from medical to retail. This technology continues to evolve, providing new opportunities to automate processes, improve security, and enhance customer service. Let’s take a look at how facial recognition is being applied in different fields.
Photo Services
Facial recognition technology in the photographic industry helps solve a number of tasks such as automatic image recognition, sorting and searching. It speeds up the processing of large volumes of photos, which is especially important for photographers working at public events such as weddings, school parties or corporate events.
Example: a Japanese company1 that provides photo services for educational and childcare centres uses facial recognition to automatically search for images featuring specific children. Parents can log in, enter their child’s name, and the system will immediately show all pictures of their child’s face. This makes it much easier to find the right pictures and increases convenience for customers.
In addition, facial recognition is used to improve security and data protection: for example, access to photos is restricted to authorised users. This helps to avoid leaks of personal information and increases privacy.
Healthcare
In healthcare, facial recognition helps to significantly improve patient registration and speed up the processing of medical information. For example, a facial recognition system can automatically identify a patient’s identity, medical history, and insurance, which speeds up the admission process in healthcare facilities.
Example: Some hospitals2 use facial recognition systems to identify patients and confirm their identity during medical procedures. This helps avoid errors and speeds up admission and hospitalisation processes. In the future, facial recognition technologies are expected to be able to detect rare diseases and even track a patient’s emotional state, for example through facial recognition to assess mood or stress reactions.
Automotive Industry
In the automotive industry, facial recognition is being used to improve the safety of drivers and passengers. One example is the implementation of facial recognition technologies for keyless access to cars, and for customising seats and mirrors depending on the owner.
Example: Hyundai is using facial recognition3 to automatically adjust seats, mirrors and displays in cars based on driver identification. Also, such technologies can be used to improve driver safety, for example by analysing facial expressions to detect signs of fatigue or stress, helping to prevent accidents.
Education
In education, facial recognition is being used to automate the attendance process in educational institutions and improve campus security. The technology can significantly speed up student and faculty registration processes and can also be used to protect against unauthorised access to academic buildings.
Example: on some university campuses, facial recognition systems4 are used to automatically record student attendance at lectures and seminars. Such systems can also be used to monitor access to the campus, preventing unauthorised persons from entering.
Financial sector
The financial sector is actively using facial recognition to ensure customer security and prevent fraud. The technology is used in opening bank accounts, authorisation in mobile apps and even ATMs.
Example: ATMs equipped with facial recognition5 allow users to access their accounts without using a card or PIN. Instead, simply look into the camera and the system will compare the face with an image in a database to confirm identity. This increases security, protecting against theft and fraud.
Security
In the security industry, facial recognition is used to control access, monitor public places and find criminals. This technology can accurately identify individuals in crowds, find missing people, or track suspected criminals.
Example: in some countries, facial recognition systems are used to monitor public places such as railway stations and airport6. This helps to detect potential criminals or find missing people. At the same time, the use of technology in public places raises debates about the legality of its use and the possibility of violating citizens' privacy rights.
Retail
In retail, facial recognition is helping to improve the customer experience and security. For example, some countries have already implemented facial recognition payment systems, avoiding the use of cards and cash.
Example: China’s Alipay has introduced a «Smile-to-Pay»7 system that allows customers to pay for in-store purchases using facial recognition. When a customer approaches a checkout counter, their face is scanned and the system automatically deducts money from their account linked to their profile. This makes the shopping process faster and more convenient for customers.
Conclusion
In the future, facial recognition is likely to continue to evolve, improving identification and personalisation processes, as well as providing a higher level of security.
Facial recognition technology continues to evolve, and its applications in various industries are becoming more popular and diverse. Every year it becomes more accurate, affordable and effective, opening up new opportunities for businesses and society. However, despite all the benefits, there are a number of ethical and legal issues associated with the use of this technology, such as the protection of personal data and the potential for misuse.
- CHI Software, Face recognition for photography services. ↩︎
- HealthITSecurity, Facial Recognition in Healthcare ↩︎
- Hyundai, Facial Recognition for Vehicle Personalization ↩︎
- CampusSafety, Facial Recognition in Education ↩︎
- CaixaBank, ATM Facial Recognition ↩︎
- NIST, FRVT Facial Recognition Testing ↩︎
- Alipay, Smile-to-Pay System ↩︎
