Face Verification vs Face Recognition: The Differences

Wondering what the differences are between face recognition and face verification? This blog highlights the differences, explores the differences in algorithms used to perform this process and offers insight into how these technologies can be used in different applications.

What is face verification?

Face verification is a way of allowing a computer or a robot to confirm that a person is who they claim to be. It’s a form of biometric authentication, which means it uses some measurable physical aspect of a body as a credential. Face verification is an important example because the face is one of the most distinctive features we have, and it’s very easy to measure from a distance.

It’s not as simple as it sounds, though. Let’s say you’re building a face-verification system for use on computers at home. You can’t ask your users to bring in snapshots of themselves; they don’t want to have their pictures taken, and you might worry about how to protect their privacy anyway. What you’d like is for them to be able to use the camera built into their PC or smartphone and get accurate results without having to do anything special: just take a picture, and if they’re who they say they are, they’re in.

How does face verification work

Face recognition works by matching a new image to one you have seen before. It is a kind of pattern matching, like the way your brain figures out that the squiggle below is an F and not a 5 (which it could also be, along with many other characters).

The software has been trained to recognize faces by being shown millions of images of faces and told which ones are the same. The training process can be sped up by making it easier for the computer to find matches: shrinking the images and rotating them and so on.

This would work reasonably well if all faces were equally easy to match. They aren’t. If you saw this for the first time, could you tell which face it matched?

For some reason, this kind of transformation makes face recognition much more difficult than it otherwise would be. The problem is that as soon as you try to match two images that look very different from each other, they will fail to match test patterns that they should match.* This is because the standard approach to face verification is based on a kind of neural network called a “classical” network, which can’t deal with such large differences between pictures.

What is face recognition?

Facial recognition is used for security purposes, to verify the identity of an individual. It can be used in security applications, such as controlling access through doors, gates or other physical barriers. It is also used in computer applications for identification and authentication purposes.

Facial recognition is part of a larger set of biometrics methods that analyze human body characteristics, including fingerprints, palm prints, iris and retinal patterns, voice recognition and facial geometry. Facial recognition can be used to identify people in photos or videos, either when the image is captured or when the image is captured.

The facial recognition system uses digital images of faces captured in images or video by one or more cameras that are then compared with each other using computer vision algorithms to find the closest matches between them. This method could be described as a computer-assisted approach since humans do not directly compare two faces but use computers to compare them for them. The biggest advantage of this technique is that it does not require any cooperation from individuals being identified which means it can be used at airports or railway stations where people are likely to resist being fingerprinted.

How does face recognition work

Face recognition is a software algorithm used to verify or identify an individual’s identity by processing a video frame or a digital image in which the individual’s face is visible.

Facial recognition is an active research area in computer vision and pattern recognition, with many applications in biometrics for access control, law enforcement, entertainment, and other areas. The term typically refers to automated systems that use specific facial features (e.g., eyes, nose, mouth, etc.) to uniquely identify or verify a person’s identity.

The technology has been developed by several companies and organizations. It is used by law enforcement agencies and commercial enterprises such as banks and telecommunications companies. The earliest work on facial recognition systems was performed in the late 1950s at the MIT A.I. Laboratory under the leadership of Frank Rosenblatt. A commercial facial recognition system was available for consumer use in 2002 after several years of development by Israeli company Face-Six. Facial recognition has been included in some mobile phone products, including Apple’s iPhone X and Samsung Galaxy S9/S9+.

Comparing instances of face recognition and face verification

Face recognition and face verification are two different problems, and the difference nearly caused the FBI to fail at an important application. The problems are different in two ways:

(1) Face verification requires you to be sure that the person seeing the picture is actually the same person who is authorized to see it; face recognition does not.

(2) With face recognition, you don’t know which face you’re looking for; with face verification, you do.

These two differences make face verification much harder than face recognition. To unscramble an egg, you only need to figure out how to unscramble one egg; to verify a claim of identity, you need to figure out how to verify one identity, and then another one, and another one, and so on. It’s like trying to solve a problem by throwing more processors at it: eventually your program will run so slowly that it doesn’t matter how many processors you have.

Face recognition has been around longer than face verification, so there is more work on it. But because of the first difference — that face recognition does not require verifying that the claimed identity matches the actual identity — there has been little work on verifying identities against pictures of faces.

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