- A
Object detection
Why wrong: Object detection can locate people in frames but lacks built-in capabilities for tracking movements over time, measuring dwell time, or creating heatmaps across video streams.
- B
Optical character recognition (OCR)
Why wrong: OCR is used to extract text from images, such as reading signs or labels, not for analyzing customer movement or behaviors.
- C
Spatial analysis
Spatial analysis is designed for tracking people in video, measuring dwell time, and generating insights like foot traffic patterns and heatmaps, making it ideal for retail analytics.
- D
Image classification
Why wrong: Image classifies an entire image into a category (e.g., 'store interior') but cannot identify individual people, track their movement, or calculate dwell time over a video sequence.
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.
A retail store wants to analyze customer movement patterns, such as dwell time in front of displays and foot traffic heatmaps, using existing surveillance cameras. Which Azure Computer Vision capability is most suitable?
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
Spatial analysis
Spatial analysis is the correct choice because it is specifically designed to analyze people's presence, movement, and interactions within a physical space using video feeds. It can measure dwell time in front of displays and generate foot traffic heatmaps by tracking individuals across camera frames, which directly matches the retail store's requirements.
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.
- ✗
Object detection
Why it's wrong here
Object detection can locate people in frames but lacks built-in capabilities for tracking movements over time, measuring dwell time, or creating heatmaps across video streams.
- ✗
Optical character recognition (OCR)
Why it's wrong here
OCR is used to extract text from images, such as reading signs or labels, not for analyzing customer movement or behaviors.
- ✓
Spatial analysis
Why this is correct
Spatial analysis is designed for tracking people in video, measuring dwell time, and generating insights like foot traffic patterns and heatmaps, making it ideal for retail analytics.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Image classification
Why it's wrong here
Image classifies an entire image into a category (e.g., 'store interior') but cannot identify individual people, track their movement, or calculate dwell time over a video sequence.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse object detection (which finds objects in a single frame) with spatial analysis (which tracks movement over time across multiple frames), leading them to pick object detection for a scenario that requires temporal and spatial tracking.
Detailed technical explanation
How to think about this question
Spatial analysis in Azure Computer Vision uses a combination of person detection, tracking, and zone/line crossing logic to compute metrics like dwell time and path heatmaps. Under the hood, it leverages deep learning models to detect human keypoints and associate them across frames using re-identification features, enabling accurate counting even in crowded scenes. A real-world scenario is a retailer using spatial analysis to optimize product placement by identifying which displays have the longest average dwell time.
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
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FAQ
Questions learners often ask
What does this AI-900 question test?
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: Spatial analysis — Spatial analysis is the correct choice because it is specifically designed to analyze people's presence, movement, and interactions within a physical space using video feeds. It can measure dwell time in front of displays and generate foot traffic heatmaps by tracking individuals across camera frames, which directly matches the retail store's requirements.
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.
About these practice questions
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Last reviewed: Jun 11, 2026
This AI-900 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-900 exam.
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