add face and tutorial

Author: laujan

articles/ai-services/content-understanding/face/overview.md

@@ -2,12 +2,12 @@
 title: Azure AI Content Understanding face overview
 titleSuffix: Azure AI services
 description: Learn about Azure AI Content Understanding face solutions.
-author: lajanuar
+author: laujan
 ms.author: quentinm
 manager: nitinme
 ms.service: azure-ai-content-understanding
 ms.topic: overview
-ms.date: 05/07/2025
+ms.date: 05/19/2025
 ms.custom: build-2025-understanding-refresh
 ---
 
@@ -27,29 +27,37 @@ This service is ideal for building secure access systems, streamlining photo man
 
 Content Understanding enables a wide range of real-world applications, including face detection, verification, identification, and large-scale content processing.
 
-**Detect faces in images**:
+##### Detect faces in images
+
 Automatically identify faces in an image and return their bounding boxes. This capability simplifies tasks like highlighting, blurring, or counting faces without manual review. Common use cases include:
+
 * Cropping detected faces for ID photos, albums, or personalized content.
 * Blurring faces to ensure privacy before sharing images publicly.
 * Counting people in event photos, crowd scenes, or security footage.
 
-**Verify if two faces match**:
-Compare a face in one image with another face or an enrolled person to determine if they belong to the same individual. This is ideal for identity verification scenarios such as photo ID checks or sign-ins. Common use cases include:
-* Verifying if a driver’s selfie matches their profile photo.
-* Confirming a student’s identity before starting an online exam.
+##### Verify if two faces match
+
+Compare a face in one image with another face or an enrolled person and determine if they belong to the same individual. This comparison feature is ideal for identity verification scenarios such as photo ID checks or sign-ins. Common use cases include:
+
+* Verifying if a driver's selfie matches their profile photo.
+* Confirming a student's identity before starting an online exam.
 * Comparing a live photo with an uploaded ID for identity confirmation.
 
-**Identify a person from their face**:
-Match a face in a photo to a saved list of people to identify them. Common use cases include:
-* Matching a patient’s face to hospital records during check-in.
+##### Identify a person from their face
+
+Match a face in a photo to a saved list of people and identify them. Common use cases include:
+
+* Matching a patient's face to hospital records during check-in.
 * Identifying a student or employee from their face photo.
 * Recognizing someone from a watch list entering a secure area.
 
-**Save faces for faster future searches**:
+##### Save faces for faster future searches
+
 Index faces from images to enable quicker searches later without needing to reprocess the original content. This feature is especially useful for recurring search scenarios. Common use cases include:
+
 * Extracting and saving faces from group photos at events to recognize returning participants in future sessions.
-* Preprocessing images from school activities or sports events to easily identify students or athletes in subsequent searches.
-* Matching a theme park visitor’s face to records from previous visits without rescanning years of archived photos.
+* Processing images from school activities or sports events to easily identify students or athletes in subsequent searches.
+* Matching a theme park visitor's face to records from previous visits without rescanning years of archived photos.
 
 ## Face capabilities
 

articles/ai-services/content-understanding/tutorial/build-person-directory.md

@@ -2,15 +2,15 @@
 title: Build a person directory with Azure AI Content Understanding Face APIs
 titleSuffix: Azure AI services
 description: Learn to build a person directory with Content Understanding Face APIs
-author: lajanuar
+author: laujan
 ms.author: quentinm
 manager: nitinme
 ms.service: azure-ai-content-understanding
 ms.topic: tutorial
-ms.date: 05/07/2025
+ms.date: 05/19/2025
 ---
 
-# Tutorial: Build a Person Directory
+# Tutorial: Build a person directory
 
 A person directory provides a structured approach to storing face data for recognition tasks. It allows you to add individual faces, search for visually similar faces, and create person profiles. You can associate faces with these profiles and match new face images to known individuals. This setup supports both flexible face matching and identity recognition across images and videos.
 
@@ -24,11 +24,11 @@ For secure and scalable access, we recommend storing all face images in Azure Bl
 
 Enrollment involves the following steps:
 
-1. Create an empty person directory
-2. Add persons
-3. Add faces and associate with a person
+1. [Create an empty person directory](#create-an-empty-person-directory)
+1. [Add persons](#add-persons)
+1. [Add faces and associate with a person](#add-faces-and-associate-with-a-person)
 
-### Step 1: Create an empty person directory
+### Create an empty person directory
 
 To create a new person directory, send a `PUT` request to the API endpoint. This directory serves as the container for storing faces and associated persons.
 
@@ -68,7 +68,7 @@ The API creates the directory and returns a confirmation response.
 }
 ```
 
-### Step 2: Add persons
+### Add persons
 
 To recognize or manage individuals, you need to create a person profile. Once created, you can associate faces with this person.
 
@@ -101,7 +101,7 @@ The API returns a `personId` that uniquely identifies the created person.
 }
 ```
 
-### Step 3: Add faces and associate with a person
+### Add faces and associate with a person
 
 You can add a face to the directory and optionally associate it with an existing person. The API supports both image URLs and base64-encoded image data.
 
@@ -130,7 +130,7 @@ Content-Type: application/json
 - `faceSource`: Specifies the face image.
   - `url`: The file path of the image stored in Azure Blob Storage.
   - `data`: Base64-encoded image data as optional alternative to `url`.
-  - `imageReferenceId`: (Optional) A user-defined identifier for the image. This can be helpful for tracking the image's origin or for mapping it to other data.
+  - `imageReferenceId`: (Optional) A user-defined identifier for the image. This identifier can be helpful for tracking the image's origin or for mapping it to other data.
   - `targetBoundingBox`: (Optional) Approximate location of the face in the image. If omitted, the API detects and uses the largest face.
 - `qualityThreshold`: (Optional) Filters face quality (`low`, `medium`, or `high`). The default is `medium`, meaning only medium or high-quality faces are stored. Lower quality faces are rejected.
 - `personId`: (Optional) The `personId` of an existing person to associate the face with.
@@ -155,8 +155,8 @@ The API returns a `faceId` that uniquely identifies the created face with the de
 
 After creating your person directory and adding face images with optional person associations, you can perform two key tasks:
 
-1. **Identify a person**: Match a face image against enrolled persons in the directory to determine the most likely identity.
-2. **Find similar faces**: Search for visually similar faces across all stored face entries in the directory.
+1. **[Identify a person](#identify-a-person)**: Match a face image against enrolled persons in the directory and determine the most likely identity.
+1. **[Find similar faces](#find-similar-faces)**: Search for visually similar faces across all stored face entries in the directory.
 
 These capabilities enable robust face recognition and similarity matching for various applications.
 
@@ -248,4 +248,5 @@ The API returns the detected bounding box of the face along with the most simila
 
 
 ## Next steps
-- Explore how to identify individuals in video content using the [Azure AI Content Understanding video solutions (preview)](../video/overview.md).
+
+Explore how to identify individuals in video content using the [Azure AI Content Understanding video solutions (preview)](../video/overview.md).