The software provides you with human identikit, using which you can assemble facial images and get particular kinds of information about a person with a similar type of face. The identikit includes the following facial features: forehead shapes, cheekbone shapes, chins, eyes, eyebrows, noses, mouths and ears. Apply facial recognition for a range of scenarios. Detect, identify, and analyze faces in images and videos. Build on top of this technology to support various scenarios—for example, authenticate people for access, count people in a space for crowd control, or garner crowd insights for media campaigns. PARTS AND WHOLES IN FACE RECOGNITION 227 search and were therefore perceived in terms of their features. In another study with Identikit faces in a simultaneous matching task, Mathews (1978). Identikit: download Identikit related software. Digital Physiognomy 1.79 Looking for a program both entertaining and enlightening? Digital Physiognomy reads a person's face and tells you about the secret character traits of that parson. Identi-Kit 7 has been redesigned to make the creation of facial composites simpler and the results more effective. Updated user interface to make the process of creating the composite sketch intuitive. New tools give the use greater control to customize the sketch and achieve even greater accuracy. 60% more facial features than previous versions.
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Warning
On June 11, 2020, Microsoft announced that it will not sell facial recognition technology to police departments in the United States until strong regulation, grounded in human rights, has been enacted. As such, customers may not use facial recognition features or functionality included in Azure Services, such as Face or Video Indexer, if a customer is, or is allowing use of such services by or for, a police department in the United States.
Important
Transport Layer Security (TLS) 1.2 is now enforced for all HTTP requests to this service. For more information, see Azure Cognitive Services security.
The Azure Face service provides AI algorithms that detect, recognize, and analyze human faces in images. Facial recognition software is important in many different scenarios, such as identity verification, touchless access control, and face blurring for privacy.
Identity Verification: Verifies someone’s identity against a government-issued ID card like a passport or driver’s license or other enrollment image to grant access to digital or physical services or recover an account. Specific access scenarios include opening a new account, verifying a worker, or administering an online assessment. Identity verification can be done once when a person is onboarded, and repeatedly as someone accesses a digital or physical service.
Touchless Access Control: Compared to today’s methods like cards or tickets, opt-in face identification enables an enhanced access control experience while reducing the hygiene and security risks from card sharing, loss, or theft. Facial recognition assists the check-in process with a human in the loop for check-ins in airports, stadiums, theme parks, or buildings as well as reception kiosks at offices, hospitals, gyms, clubs, or schools.
Face Redaction: Redact or blur detected faces of people recorded in a video to protect their privacy.
This documentation contains the following types of articles:
- The quickstarts are step-by-step instructions that let you make calls to the service and get results in a short period of time.
- The how-to guides contain instructions for using the service in more specific or customized ways.
- The conceptual articles provide in-depth explanations of the service's functionality and features.
- The tutorials are longer guides that show you how to use this service as a component in broader business solutions.
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Face detection and analysis
Face detection is required as a first step in all the other scenarios. The Detect API detects human faces in an image and returns the rectangle coordinates of their locations. It also returns a unique ID that represents the stored face data, which is used in later operations to identify or verify faces.
Optionally, face detection can also extract a set of face-related attributes, such as head pose, age, emotion, facial hair, and glasses. These attributes are general predictions, not actual classifications. Some attributes are useful to ensure that your application is getting high-quality face data when users add themselves to a Face service (for example, your application could advise users to take off their sunglasses if the user is wearing sunglasses).
Note
The face detection feature is also available through the Computer Vision service. However, if you want to use other Face operations like Identify, Verify, Find Similar, or Face grouping, you should use this service instead.
For more information on face detection and analysis, see the Face detection concepts article. Also see the Detect API reference documentation.
Identity verification
Modern enterprises and apps can use the the Face identification and Face verification operations to verify that a user is who they claim to be. Face identification can be thought of as 'one-to-many' matching. Match candidates are returned based on how closely their face data matches the query face. This scenario is used in granting building access to a certain group of people or verifying the user of a device.
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The following image shows an example of a database named 'myfriends'. Each group can contain up to 1 million different person objects. Each person object can have up to 248 faces registered.
After you create and train a group, you can do identification against the group with a new detected face. If the face is identified as a person in the group, the person object is returned.
Verification
The verification operation answers the question, 'Do these two faces belong to the same person?'. Verification is also called 'one-to-one' matching because the probe face data is compared to only a single enrolled face. Verification is used in the identification scenario to double-check that a given match is accurate.
For more information about identity verification, see the Facial recognition concepts guide or the Identify and Verify API reference documentation.
Find similar faces
The Find Similar operation does face matching between a target face and a set of candidate faces, finding a smaller set of faces that look similar to the target face. This is useful for doing a face search by image.
The service supports two working modes, matchPerson and matchFace. The matchPerson mode returns similar faces after filtering for the same person by using the Verify API. The matchFace mode ignores the same-person filter. It returns a list of similar candidate faces that may or may not belong to the same person.
The following example shows the target face:
And these images are the candidate faces:
To find four similar faces, the matchPerson mode returns a and b, which show the same person as the target face. The matchFace mode returns a, b, c, and d—exactly four candidates, even if some aren't the same person as the target or have low similarity. For more information, see the Facial recognition concepts guide or the Find Similar API reference documentation.
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Group faces
The Group operation divides a set of unknown faces into several smaller groups based on similarity. Each group is a disjoint proper subset of the original set of faces. It also returns a single 'messyGroup' array that contains the face IDs for which no similarities were found.
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All of the faces in a returned group are likely to belong to the same person, but there can be several different groups for a single person. Those groups are differentiated by another factor, such as expression, for example. For more information, see the Facial recognition concepts guide or the Group API reference documentation.
Sample app
The following sample applications show a few ways to use the Face service:
- FamilyNotes UWP app is a Universal Windows Platform (UWP) app that uses face identification along with speech, Cortana, ink, and camera in a family note-sharing scenario.
Data privacy and security
As with all of the Cognitive Services resources, developers who use the Face service must be aware of Microsoft's policies on customer data. For more information, see the Cognitive Services page on the Microsoft Trust Center.
Next steps
Follow a quickstart to code the basic components of a face recognition app in the language of your choice.
- Client library quickstart.