- A
Image Classification
Why wrong: Image Classification assigns a label to an entire image (e.g., 'display'), but it cannot track a person's movement over time or detect whether they pick up an item.
- B
Optical Character Recognition (OCR)
Why wrong: OCR reads printed or handwritten text from images. It is not designed for tracking people or analyzing interactions with objects.
- C
Object Detection
Why wrong: Object Detection can locate and identify objects (including people) in a single frame, but it does not track movement across frames or measure dwell time. It lacks temporal analysis.
- D
Spatial Analysis
Spatial Analysis is a computer vision capability specifically designed for analyzing people's presence, movement, and interactions within a physical space. It can measure dwell time and detect actions like a person reaching for an item, making it the correct choice for this scenario.
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 behavior in front of a specific product display. They need to determine how long each customer stands in front of the display and whether they pick up an item. Which Azure Computer Vision capability should they 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
Spatial Analysis
Spatial Analysis is the correct Azure Computer Vision capability because it is specifically designed to analyze people's movement, presence, and interactions within a physical space using video feeds. It can track how long a customer stands in front of a display (dwell time) and detect actions like picking up an item, by processing bounding boxes and skeleton data from cameras.
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.
- ✗
Image Classification
Why it's wrong here
Image Classification assigns a label to an entire image (e.g., 'display'), but it cannot track a person's movement over time or detect whether they pick up an item.
- ✗
Optical Character Recognition (OCR)
Why it's wrong here
OCR reads printed or handwritten text from images. It is not designed for tracking people or analyzing interactions with objects.
- ✗
Object Detection
Why it's wrong here
Object Detection can locate and identify objects (including people) in a single frame, but it does not track movement across frames or measure dwell time. It lacks temporal analysis.
- ✓
Spatial Analysis
Why this is correct
Spatial Analysis is a computer vision capability specifically designed for analyzing people's presence, movement, and interactions within a physical space. It can measure dwell time and detect actions like a person reaching for an item, making it the correct choice for this scenario.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse Object Detection (which only identifies objects in a static frame) with Spatial Analysis (which tracks movement and actions over time), leading them to pick Option C because they think detecting a person and an item is sufficient, but they miss the temporal and action-based requirements.
Detailed technical explanation
How to think about this question
Spatial Analysis uses a combination of computer vision and deep learning models (e.g., pose estimation and object tracking) to process video frames in real time, outputting events like 'PersonEnteredZone' or 'PersonLeftZone' with timestamps. Under the hood, it leverages Azure Video Indexer and the Azure Cognitive Services container for on-premises deployment, enabling privacy-compliant analysis without sending video data to the cloud. A real-world scenario is retail stores using it to optimize product placement by measuring engagement heatmaps.
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-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 Azure Computer Vision capability because it is specifically designed to analyze people's movement, presence, and interactions within a physical space using video feeds. It can track how long a customer stands in front of a display (dwell time) and detect actions like picking up an item, by processing bounding boxes and skeleton data from cameras.
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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