AI-102 Implement computer vision solutions Practice Question
A security company uses Azure AI Face API to analyze surveillance footage. They need to detect faces in low-light images and obtain face bounding boxes, but they do not need to identify individuals. They also want to minimize cost and avoid unnecessary features. Which Face API operation should they call?
⚠ Common exam trap
The trap here is thinking that face detection always requires face IDs, when in fact face IDs are only needed for identification or verification and can be disabled to reduce cost.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Face - Detect with returnFaceId=false and returnFaceLandmarks=false
To detect faces without identification, the Face - Detect operation should be called with returnFaceId and returnFaceLandmarks set to false. This returns bounding boxes and avoids the cost of generating face IDs. Identify and Verify are for matching or comparing identities, which are not needed here, and enabling face IDs or landmarks adds unnecessary expense.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Face - Detect with returnFaceId=true and returnFaceLandmarks=true
Why it's wrong here
Enabling returnFaceId generates a unique face ID, which is used for identification and verification. This adds cost and is unnecessary when the goal is only detection. Landmarks provide facial feature points but also add overhead. The scenario explicitly states that identification is not needed, so requesting face IDs and landmarks increases cost and complexity without benefit.
- ✗
Face - Verify with two face IDs
Why it's wrong here
Verify checks whether two faces belong to the same person, which is a one-to-one comparison. It requires face IDs from prior detection calls and is used for authentication or similarity checks. This scenario only requires detecting faces in images, not verifying identities. Using Verify would add unnecessary steps and cost, and it does not provide bounding boxes for all faces in an image.
- ✓
Face - Detect with returnFaceId=false and returnFaceLandmarks=false
Why this is correct
This operation returns face bounding boxes without generating face IDs or landmarks, which is exactly what is required for detection only. It minimizes cost because face ID generation is a billable feature. By setting both parameters to false, the response includes only the rectangle coordinates and basic attributes if requested, aligning with the need to detect faces in low-light images without identifying individuals.
- ✗
Face - Identify with a person group
Why it's wrong here
The Identify operation matches detected faces against a person group to determine identity. This requires creating and training a person group, and it returns candidate identities. The company does not need to identify individuals, so this operation is overkill and would incur additional cost and setup. It also requires face IDs, which are not needed for simple detection.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
This AI-102 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-102 exam.