AI-900 Practice Question: Describe features of computer vision workloads on Azure
This AI-900 practice question tests your understanding of describe features of computer vision workloads on azure. 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.
What can Azure AI Vision's spatial analysis feature do?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Analyze video to detect people's presence and movement in physical spaces
Azure AI Vision's spatial analysis feature is designed to analyze video streams from cameras to detect the presence and movement of people in physical spaces. It uses computer vision models to track individuals, count occupancy, and understand movement patterns in real-time, enabling applications like retail analytics or workplace safety.
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.
✗
Extract text from documents and images
Why it's wrong here
Text extraction is OCR — spatial analysis tracks people's presence and movement in physical spaces from video.
✓
Analyze video to detect people's presence and movement in physical spaces
Why this is correct
Spatial analysis uses computer vision on video to count people, track movements, and monitor occupancy in physical environments.
Related concept
Read the scenario before looking for a memorised answer.
✗
Identify the 3D coordinates of objects in satellite imagery
Why it's wrong here
3D mapping is a geospatial task — spatial analysis tracks people in video for retail and facility management use cases.
✗
Generate 3D models from 2D photographs
Why it's wrong here
3D reconstruction is photogrammetry — spatial analysis analyzes video for people detection and movement.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse spatial analysis with general computer vision features like OCR or 3D reconstruction, assuming it can handle any image or video analysis task, when it is specifically focused on people detection and movement in physical spaces from live or recorded camera feeds.
Detailed technical explanation
How to think about this question
Spatial analysis leverages deep learning models trained on human pose estimation and object tracking, processing video frames to output JSON metadata with bounding boxes, centroids, and track IDs for each detected person. It can be configured with operations like 'personCount' or 'personCrossingLine' to trigger events when people enter or exit zones, making it valuable for real-time occupancy monitoring in smart buildings or retail stores.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AI-900 question in full detail.
Describe features of computer vision workloads on Azure — This question tests Describe features of computer vision workloads on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Analyze video to detect people's presence and movement in physical spaces — Azure AI Vision's spatial analysis feature is designed to analyze video streams from cameras to detect the presence and movement of people in physical spaces. It uses computer vision models to track individuals, count occupancy, and understand movement patterns in real-time, enabling applications like retail analytics or workplace safety.
What should I do if I get this AI-900 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.
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Question Discussion
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