- A
Azure AI Video Indexer sentiment analysis
Why wrong: Analyzes emotions, not location.
- B
Azure AI Video Indexer people detection and tracking
Tracks people movements and can trigger alerts.
- C
Azure AI Face identify API
Why wrong: Identifies faces, not location.
- D
Object detection in Azure AI Vision
Why wrong: Detects objects but not their movement or location over time.
Question 37 of 993
How to Detect People in Restricted Areas Using Azure Video Indexer
This AI-102 practice question tests your understanding of implement computer vision solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are developing a solution that uses Azure AI Video Indexer to analyze surveillance videos for suspicious activity. The solution must generate alerts when a person is detected in a restricted area. Which feature should you use?
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
✓
Azure AI Video Indexer people detection and tracking
Azure AI Video Indexer's people detection and tracking feature is specifically designed to detect and track individuals across video frames, making it ideal for generating alerts when a person enters a restricted area. This feature provides bounding boxes, timestamps, and tracking IDs that enable real-time monitoring and alerting based on spatial rules.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure AI Video Indexer sentiment analysis
Why it's wrong here
Analyzes emotions, not location.
- ✓
Azure AI Video Indexer people detection and tracking
Why this is correct
Tracks people movements and can trigger alerts.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure AI Face identify API
Why it's wrong here
Identifies faces, not location.
- ✗
Object detection in Azure AI Vision
Why it's wrong here
Detects objects but not their movement or location over time.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse generic object detection (which can detect people as objects) with the dedicated people tracking capability that provides persistent IDs and temporal continuity needed for restricted-area alerts.
Detailed technical explanation
How to think about this question
Azure AI Video Indexer's people detection uses a combination of object detection and re-identification algorithms to assign unique tracking IDs to individuals across frames, even when they leave and re-enter the scene. This enables persistent tracking and can be combined with custom logic (e.g., polygon-based restricted zones) to trigger alerts. In a real-world scenario, you would use the 'people' insight in the Video Indexer API to extract coordinates and timestamps, then evaluate if a tracked person's bounding box intersects with a predefined restricted area polygon.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement computer vision solutions — This question tests Implement computer vision solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure AI Video Indexer people detection and tracking — Azure AI Video Indexer's people detection and tracking feature is specifically designed to detect and track individuals across video frames, making it ideal for generating alerts when a person enters a restricted area. This feature provides bounding boxes, timestamps, and tracking IDs that enable real-time monitoring and alerting based on spatial rules.
What should I do if I get this AI-102 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
2 more ways this is tested on AI-102
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. You need to analyze a video stream from a security camera to count the number of people entering a building. Which Azure AI service is most suitable?
easy- ✓ A.Azure AI Spatial Analysis
- B.Azure AI Custom Vision
- C.Azure AI Computer Vision
- D.Azure AI Video Indexer
Why A: Azure AI Spatial Analysis is the most suitable service because it is purpose-built for real-time spatial analysis of video streams, including counting people entering a building. It can process live camera feeds and detect when people cross a line or enter a zone, providing real-time counts. In contrast, Azure AI Video Indexer is designed for analyzing recorded video files, not live streams, making it less suitable for real-time security camera analysis. Other options like Custom Vision and Computer Vision are for image classification and image analysis, respectively, not optimized for video streams.
Variation 2. You need to analyze a live video stream from a security camera to detect people entering a restricted area. Which Azure AI service should you use?
easy- A.Azure Video Indexer
- B.Azure AI Custom Vision
- ✓ C.Azure Video Analyzer for Media (deprecated)
- D.Azure AI Face API
Why C: Azure Video Analyzer for Media (formerly Video Indexer) supports live video stream analysis for detecting people entering a restricted area. It provides pre-built AI models for person detection in live streams. Azure Video Indexer is designed for recorded videos, not live streams. Custom Vision requires custom training, and Face API is limited to facial recognition.
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Last reviewed: Jul 4, 2026
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