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 uses security cameras to analyze customer behavior. They need to detect when a person enters a specific zone (e.g., an aisle) and count how many people are in that zone at any given time. Which Azure Computer Vision capability should they use?
Correct. Spatial Analysis provides real-time tracking of people in a zone, including entry detection and head counts.
B
Object Detection
Why wrong: Incorrect. Object Detection can find people in a single image frame but does not inherently perform zone-based counting or tracking over time.
C
Image Classification
Why wrong: Incorrect. Image Classification assigns a single label to the entire image, not zone-based people counting.
D
Optical Character Recognition (OCR)
Why wrong: Incorrect. OCR extracts text from images, which is not relevant to people counting or zone detection.
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 Azure Computer Vision capability because it is specifically designed to analyze video feeds from cameras to detect people entering predefined zones, track their movement, and count occupancy in real time. This capability uses AI models to understand spatial relationships and events within a video frame, such as a person crossing a line or entering a zone, which directly matches the requirement to detect when a person enters a specific aisle and count how many people are in that zone.
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.
✓
Spatial Analysis
Why this is correct
Correct. Spatial Analysis provides real-time tracking of people in a zone, including entry detection and head counts.
Related concept
Read the scenario before looking for a memorised answer.
✗
Object Detection
Why it's wrong here
Incorrect. Object Detection can find people in a single image frame but does not inherently perform zone-based counting or tracking over time.
✗
Image Classification
Why it's wrong here
Incorrect. Image Classification assigns a single label to the entire image, not zone-based people counting.
✗
Optical Character Recognition (OCR)
Why it's wrong here
Incorrect. OCR extracts text from images, which is not relevant to people counting or zone detection.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Object Detection with Spatial Analysis because both can detect people in a frame, but Object Detection lacks the temporal and spatial reasoning (zone/line crossing, tracking, counting) required for this scenario.
Detailed technical explanation
How to think about this question
Spatial Analysis uses a combination of person detection, tracking, and zone/line crossing logic, leveraging deep learning models optimized for video streams. Under the hood, it processes frames at a configurable rate (e.g., 5 FPS) and uses a Kalman filter or similar tracking algorithm to maintain person IDs across frames, enabling accurate counting even when people occlude each other. A real-world scenario where this matters is in retail analytics for heat mapping and queue management, where the system must distinguish between a person pausing near a shelf versus actually entering the zone to avoid false positives.
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: Spatial Analysis — Spatial Analysis is the correct Azure Computer Vision capability because it is specifically designed to analyze video feeds from cameras to detect people entering predefined zones, track their movement, and count occupancy in real time. This capability uses AI models to understand spatial relationships and events within a video frame, such as a person crossing a line or entering a zone, which directly matches the requirement to detect when a person enters a specific aisle and count how many people are in that zone.
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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