Understand facial analysis

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  • 2 minutes

Face detection involves identifying regions of an image that contain a human face, typically by returning bounding box coordinates that form a rectangle around the face, like this:

An image with two faces highlighted in rectangles

With Face analysis, facial features can be used to train machine learning models to return other information, such as facial features such as nose, eyes, eyebrows, lips, and others.

facial landmarks image showing data around face characteristics

Facial recognition

A further application of facial analysis is to train a machine learning model to identify known individuals from their facial features. This is known as facial recognition, and uses multiple images of an individual to train the model. This trains the model so that it can detect those individuals in new images on which it wasn't trained.

A person identified as "Wendell"

When used responsibly, facial recognition is an important and useful technology that can improve efficiency, security, and customer experiences. Next we'll explore Azure AI Face service, which provides pre-trained models to detect, recognize, and analyze faces.

Next unit: Get started with facial analysis on Azure

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