Face Recognition

Face Recognition
Product Introduction
Product Documentation©2013-2022 Tencent Cloud. All rights reserved.

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Face Recognition

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Face Recognition

Contents
Product Introduction
Overview
Strengths
Use Cases©2013-2022 Tencent Cloud. All rights reserved.

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Face Recognition

Product Introduction
Overview：

Last updated 2023-12-27 15:39:14

Overview
Tencent Cloud Face Recognition leverages Tencent YouTu's face recognition and analysis technologies to provide
developers and enterprises with a full set of high-performance and high-availability face recognition services such asdetection, analysis, search, comparison, verification, feature localization, and liveness detection. It is applicable toscenarios such as smart retail, smart community, online entertainment, smart buildings, and online identity verification,
meeting the needs for facial attribute recognition and identity verification across industries.

Features
Face detection and analysis
Face Recognition can analyze a given image to determine whether it contains a face. If yes, it can return information
about the position, attributes, and quality of the face. This includes gender, age, expression, charm, glasses, hair,mask, pose, quality ranking, etc. For more information, please see Face Detection and Analysis.

Facial feature localization
Face Recognition can locate facial features on a given image and calculate 90 facial landmarks. This includes
eyebrows (8 points on each side), eyes (8 points on each side), nose (13 points), mouth (22 points), face contour (21points), and eyeballs or pupils (2 points). For more information, please see Facial Feature Localization.

Face comparison
Face Recognition can compare faces in two images and return the similarity score. For more information, please see
Face Comparison.
If you need to check "whether the person is someone" in scenarios such as face log-in, i.e., whether the person in agiven image is someone with a known identity, we recommend using Face Verification.

Group management
Face Recognition allows you to create a group to store information about people (such as facial features and IDs) for
face verification and face search. For more information, please see Group Management APIs.

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Face verification
Face Recognition can check whether a person in an image corresponds to a given PersonId . For more
information on PersonId , please see Group Management APIs. For more information, please see Face
Verification.
Unlike the CompareFace API that is used to compare the similarity of two faces, face verification is used to check"whether the person in a given image is the same as the PersonId " whose information is stored in a group. This
PersonId may have multiple face images.

Face search
Face Recognition can recognize the first N people in one or more groups who are similar to the person in a given
image and rank the similarity in descending order. Each search supports up to 3 million faces in such groups. The
search can be made on one or more faces in the image. For more information, please see Face Search.

Image-based liveness detection
Image-based liveness detection is used to detect the liveness of faces in images uploaded by the user (i.e., whether
the person in the image is real). Compared to video-based liveness detection, image-based detection does not require
speaking, shaking heads, winking, etc. It is only suitable for scenarios where requirements for attack defense are nothigh. For more information, please see Image-based Liveness Detection.

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Strengths：

Last updated 2023-12-27 15:40:11

Strengths
Accurate recognition
Face Recognition has set many records in international competitions. It achieved an 99.80% accuracy in LFW 2017and an 83.29% recognition rate in the MegaFace challenge.

Stability and reliability
Face Recognition has been verified by a large number of users and complex use cases. It is proven to be highly
reliable and robust with service availability up to 99.9%.

Leading algorithms
Based on the 3rd generation Tencent YouTu Grandmother Model, Face Recognition has integrated multiple training
methods to optimize the model, including metric learning, transfer learning, multi-task learning, etc. It can custom finetuning or distilling models to meet requirements for performance and latency in different scenarios.

Diverse use cases
Face Recognition provides simple APIs and has diverse use cases such as access control, VIP identification, sign-in,payment and login.

Real-time response
Face Recognition features high concurrence, high throughput, and low latency. It can search and process millions offaces in hundreds of milliseconds, meeting you needs in real time.

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Use Cases：

Last updated 2023-12-27 15:40:30

Use Cases
Business
VIP customer management
Face search technology can be used to recognize VIP customers in an image, improving VIP customer services andstrengthening relationships.
Traffic monitoring
Face detection technology can be used to count the number of people on screen. It is suitable not only for the retailindustry to analyze the effectiveness of product placement, but also schools, workplaces, conferences, etc. to track
attendance.
Precise ad placement
Face analysis technology can be used to quickly and accurately analyze people attributes in images, such as age andgender, and facilitate targeted advertising.

Entertainment
Photo classification
Face Recognition uses face recognition and search technologies to group similar faces in an album and organize
photos by faces.
Beauty filters
Face Recognition uses the feature localization technology to accurately detect facial features and apply beauty filters,
reshape or swap faces, add cartoon effects or stickers, etc.

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