What Is Facial Recognition
Facial recognition is an artificial intelligence technology that identifies or verifies a person's identity from the unique features of their face, comparing an image or video captured by a camera against a database of previously registered faces. It's not the same as simple face detection: detecting a face only confirms there's a face in the image, while facial recognition answers the question "whose face is this?"
Today it's used to unlock phones, control access to offices and factories, speed up lines at airports, and increasingly, as an extra layer of security for businesses that used to rely only on cards or passwords.
How Facial Recognition Works: the Technical Pipeline
Explaining how facial recognition works is easier if we break it into three stages that happen in seconds, almost always in this order:
1. Detection
The system scans the image or video frame and locates where a face is, without yet knowing whose it is. Current models can detect multiple faces at once, even with movement, different angles, or changing lighting.
2. Feature Extraction (Embedding)
Once a face is located, a neural network model converts its distinctive features (distance between the eyes, jawline shape, nose contour, among dozens of other points) into a numeric vector known as a facial embedding. This vector is a compact mathematical representation of the face, not a photograph or data you can "read" at a glance.
3. Comparison or Match
The system compares that embedding against the ones already stored in its database, using a distance or similarity measure. If the similarity clears a defined threshold, the system reports a match; if not, it reports that the person isn't registered. That threshold is adjustable and defines the balance between security and convenience: a very strict threshold rejects more valid faces, while a very loose one lets through more false positives.
How Accurate Is Facial Recognition: Factors That Affect the Result
Facial recognition accuracy isn't a fixed number: it depends on conditions that change from one installation to another. The factors that matter most are:
- Camera quality and image resolution. A low-resolution camera or one with aggressive compression loses the detail the model needs to generate a reliable embedding.
- Lighting. Backlighting, harsh shadows, or low light reduce accuracy, especially at outdoor entrances or with changing natural light.
- Face angle and distance. Models work best with faces looking straight at the camera and at a reasonable distance; sharp angles or partially covered faces lower the confidence of the match.
- Quality and size of the reference database. The more complete and up to date each person's reference photos are, the more reliable the comparison.
- The algorithm and the configured similarity threshold. Not every model performs the same way, and the threshold chosen by whoever implements the system directly changes both the hit rate and the false-positive rate.
That's why, when a business evaluates facial recognition, the right question isn't "how accurate is it in general?" but "how accurate is it under the real conditions where I'm going to use it?"
Facial Recognition in Businesses: Real Use Cases
Facial recognition in businesses is mainly used in three areas:
- Access control. It replaces or complements cards and codes at offices, industrial plants, and buildings, reducing the risk of someone lending their credential to another person.
- Attendance tracking. It logs employee check-ins and check-outs without physical time clocks or fingerprint readers, which also avoids the wear and tear of contact-based biometric readers.
- Security and loss prevention. In retail and warehouses, some systems flag a match against an internal watch list as support for security teams.
If your business is already evaluating a specific access-control rollout, at AISDC we document a concrete use case on our biometric access control page, distinct from this introductory guide because it focuses on the physical installation in a building or plant.
Facial Recognition Advantages and Disadvantages
Before deciding whether to implement it, it's worth weighing the pros and cons of facial recognition:
Advantages:
- Reduces identity fraud compared to cards or passwords, which can be lent, lost, or stolen.
- Speeds up high-traffic entry points, with no line to tap a reader or type a code.
- Removes physical contact with the device, which matters in environments where hygiene is a priority.
- Generates a digital access log useful for security audits.
Disadvantages:
- Requires cameras, computing power, and in many cases stable connectivity, which means an upfront investment.
- Accuracy drops under poor lighting or with partially covered faces.
- Handles biometric data, which Mexican law classifies as sensitive information requiring careful handling, as explained in the next section.
- Can create pushback from employees or customers if the business doesn't clearly communicate what the data is used for and who has access to it.
Privacy and the Legal Framework for Facial Recognition in Mexico
A person's face, and the embedding generated from it, are biometric data. The Ley Federal de Protección de Datos Personales en Posesión de los Particulares (LFPDPPP), Mexico's federal data protection law for private parties, classifies biometric data as sensitive personal data, alongside health data, ethnic origin, or preferences, because misusing it can seriously harm the person it belongs to.
This has practical consequences for any business that wants to use facial recognition:
- It needs a specific privacy notice that clearly explains what biometric data it collects, what it's used for, and how long it's kept.
- It must get each person's express consent before capturing and storing their face, except for the exceptions the law itself sets out.
- It must implement reasonable security measures to protect that data, since a biometric data leak is more serious than a password leak: you can't "change" a face the way you change an access code.
After INAI, the autonomous body that oversaw this, was dissolved in 2025, oversight of personal data protection in Mexico moved into the federal government itself. If your business handles biometric data, it's worth reviewing the current state of this regulation with legal counsel before implementing any system, rather than assuming the rules from a few years ago still apply exactly as they did.
How to Implement Facial Recognition Responsibly
For a facial recognition project to work well and comply with the law, it helps to follow a clear order:
- Define the specific use case (access control, attendance, security) before choosing the technology.
- Draft and publish the corresponding privacy notice and get people's consent before capturing their face.
- Choose cameras and locations that guarantee good lighting and a frontal angle, to maximize accuracy.
- Set the similarity threshold according to the security level each access point needs.
- Define who has access to the face database and what security controls protect it.
This same "identify before you automate" approach applies to other computer vision technologies that process images or video to make automated decisions, and it's worth reviewing alongside your broader enterprise security strategy.
Frequently Asked Questions
What is facial recognition and how is it different from face detection?
Facial recognition identifies who a person is by comparing their face against a database, while face detection only confirms a face is present in the image, without identifying anyone.
Is it legal to use facial recognition in a business in Mexico?
Yes, as long as the business complies with the LFPDPPP: it must disclose in a privacy notice what biometric data it collects and get each person's express consent before capturing their face.
How reliable is facial recognition in practice?
It depends on camera quality, lighting, face angle, and the configured similarity threshold; that's why the same system can perform very differently across two different installations.
What's the difference between facial recognition and biometrics in general?
Facial recognition is one specific type of biometrics, which also includes fingerprint, iris, or voice; they all share the trait of identifying a person by a unique physical characteristic — more in our guide on what biometrics is.
Can facial recognition be used together with physical access control?
Yes, that's one of its most common uses: it replaces or complements cards and codes at doors and turnstiles, something we cover in more depth in our guide on what access control is.
If your business is evaluating facial recognition for access control, attendance, or security, and you want to do it in compliance with the LFPDPPP from the design stage, at AISDC we build facial recognition solutions adapted to the real conditions of your operation.