What Is Facial Recognition?

Key takeaways

Facial recognition identifies a person by analyzing their facial features, and the term also refers to the software that automates the process. 

• The facial recognition industry is growing, with an anticipated US market value of $47 billion by 2031 [1].

• Organizations can use facial recognition to give access to buildings or devices, monitor attendance at school or work, confirm identity to reduce the risk of fraud, and enhance the customer experience with personalized recommendations.

• You can use facial recognition while working in various roles, including machine learning engineer, software developer, and visualization artist.

Learn more about facial recognition, how organizations use it today, and some of the careers you can pursue in this field. If you’re ready to build your skills in this emerging field, consider enrolling in the IBM Machine Learning Specialization. You’ll have the opportunity to learn how to compare and contrast different machine learning algorithms in as little as three months. Upon completion, you’ll have earned a career credential to feature on your resume.

Types of facial recognition software

Two broad categories used to classify facial recognition software are holistic and feature-based, terms describing the process used to analyze faces. Holistic models examine your entire face and compare your features to those in images stored in a database. A feature-based model analyzes your face more deeply, such as considering measurements between features and the contours of bones.

You can also sort facial recognition by the techniques used to capture an image. If you're using a camera-based model, you take a picture of yourself using the camera on your device. Each time you attempt to unlock the device, you turn on the camera and let the software compare the live image to the stored image to verify your identity. Infrared-based models work similarly, but they use infrared sensors to capture a 3D image of your face. An important advantage of this model is that the cameras work in dim light and are more secure.

How facial recognition works

Facial recognition software typically follows a three-step process: detection, analysis, and recognition.

• Detect: In the first step, the program searches through an image looking for facial data. It views faces from the front and side, looking for distinctive features to analyze in the next step.

• Analyze: After identifying a face in an image, the program examines facial landmarks like the distance from the chin to the forehead and between the eyes. It also considers the shape of different features like the cheekbones, lips, ears, and more.

• Recognize: In the final step of the process, the facial recognition program applies what it has learned from the data to verify an individual's identity. It may compare the current image under analysis with a stored image, like one used on a government ID.

What part of the brain is responsible for facial recognition​?

The fusiform face area (FFA), located in the fusiform gyrus of your temporal lobe, is responsible for facial recognition. This area helps you process human faces and interpret facial expressions. This area actually seems to be solely devoted to facial recognition, making it an area of interest for scientists in this field.

What is facial recognition used for?

Facial recognition software has multiple uses, including protecting access to sensitive information, confirming identity, and preventing fraud. What was once only seen in sci-fi flicks now has applications in your daily life. The following list highlights some ways you may see people and organizations using facial recognition technology:

• Access control: Verify identity before granting access to devices, buildings, and documents.

• Attendance: Scan people as they enter a facility to create an attendance record for work or school. 

• Banking: Confirm a customer's identity at ATMs and banking centers to prevent fraud.

• Customer experience: Notify authorities when known shoplifters are in stores, suggest products for customers, and allow customers to pay for purchases. 

• Health care: Improve infection control by reducing the number of touchpoints in a facility, identifying genetic diseases, and monitoring patients.

• Investigations: Assist detectives during investigations and ensure officers have arrested the correct individuals.

• Security: Confirm the identity of individuals, track movements, and prevent unauthorized access to sensitive locations and equipment. 

• Transportation: Verify passengers' identity at airports and border crossings to increase convenience and security. 

Read more: AI in Health Care: Applications, Benefits, and Examples

Who uses facial recognition?

Several types of organizations use facial recognition software to confirm a person's identity, including law enforcement and banks. Personnel working in airports and border control may use facial recognition to verify the identity of individuals traveling to and entering the United States. Cell phone and computer users may rely on facial recognition capabilities to restrict device access and protect sensitive information. Some retailers and bankers install facial recognition systems to customize the customer experience and prevent theft. 

What is biometric facial recognition?

Biometric facial recognition is a type of technology used to verify your identity based on your unique facial features. These systems can identify and verify people in real time, making it an efficient and convenient form of security.

Pros and cons of using facial recognition

Fans of facial recognition typically appreciate the convenience it offers, while less enthusiastic people may raise questions about privacy. However, the benefits and drawbacks of using facial recognition extend beyond these top points. Here are more pros and cons of using facial recognition.

Pros of facial recognition

Facial recognition offers several advantages over other biometric screening and access control types. It tends to be quicker and easier to use than fingerprint analysis or retina scans since capturing your face in the camera lens is usually less complicated than lining up your fingertip on a device's scanner. Facial recognition is usually more secure than passwords and personal identification numbers (PINs), which someone can guess, and it has greater accuracy than other authentication methods like phone numbers and email addresses. Facial recognition technology often integrates more easily with existing security software.

Cons of facial recognition

Privacy is one of the top concerns surrounding facial recognition, and several states have passed laws restricting where organizations can use the software and what they do with the data they collect from it. The threat of a data breach is troublesome because facial features cannot be changed like a password or PIN, increasing the danger of identity theft if someone has access to facial recognition data. Some organizations have raised questions about the accuracy of facial recognition software, as others have noted the software sometimes has problems confirming the identity of individuals with darker skin. This issue can lead to a greater number of false positives. 

How to get started in facial recognition

Your first steps toward a career in facial recognition depend on the type of work you want to do. For example, you may learn how to code if you want to design facial recognition software. This means your path toward a career in facial recognition will likely look different from someone else's. Fortunately, the future of the facial recognition market looks promising. It should continue to grow over the next few years, and analysts anticipate a value of $47 billion by 2031 [1].

A facial recognition analyst makes a median total pay of $92,000 annually [2]. This figure includes base salary and additional pay, which may represent profit-sharing, commissions, bonuses, or other compensation. You'll likely need a graduate degree and specialized training to qualify for this job. You can also find more career options in the field. The following list highlights the variety of facial recognition jobs available and salary details.

All salary information represents the median total pay from Glassdoor as of December 2025. These figures include base salary and additional pay, which may represent profit-sharing, commissions, bonuses, or other compensation.

• Image processing engineer: $129,000[3]

• Machine learning engineer: $159,000 [4]

• Pattern recognition engineer: $135,000 [5]

• Software developer: $121,000 [6]

• Software sales: $205,000 [7]

• Visualization artist: $119,000 [8]

Explore free resources to build your career

Learn more about emerging trends and AI industry insights by subscribing to Career Chat, our LinkedIn newsletter. Then, check out these resources for even more support:

• Bookmark this page: Artificial Intelligence Glossary: Learn AI Vocabulary 

• Explore your options: 6 Machine Learning Certificates and How to Choose the Right One for You 

• Consider your path: AI Career Quiz: Is It Right for You? Find Your Role 

Accelerate your career growth with a Coursera Plus subscription. When you enroll in either the monthly or annual option, you’ll get access to over 10,000 courses. 

Build job-ready skills with Coursera Plus

Start 7-day free trial

• 
• 
• 
• 

Start 7-day free trial