The answer is Spatial Analysis, the dedicated Azure Computer Vision capability for people counting, zone tracking, and direction detection. This is correct because Spatial Analysis processes video feeds from cameras using AI models trained specifically to identify human presence, measure occupancy within defined zones, and calculate movement trajectories—going beyond generic object detection to deliver the precise spatial metrics a retail store needs. On the AI-900 exam, this question tests your understanding of how Computer Vision services are specialized; a common trap is choosing “Object Detection” or “Face Detection,” which lack zone-based counting and directional tracking. Remember the memory tip: “Spatial” equals “space and path”—if the scenario involves counting people inside a zone or following their direction, Spatial Analysis is the only fit.
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 company wants to use security cameras to analyze customer flow. They need to detect when a person enters a specific store zone, count how many people are in that zone at any given time, and track the direction each person moves within the zone. Which Azure Computer Vision capability should they use?
Why wrong: Object detection can detect people in frames, but it does not track their movement across frames or count them entering/leaving specific zones.
B
Spatial Analysis
Spatial Analysis enables real-time analysis of people movement and occupancy in defined zones, making it ideal for this requirement.
C
Optical Character Recognition (OCR)
Why wrong: OCR extracts text from images and is unrelated to detecting people or tracking movement.
D
Semantic segmentation
Why wrong: Semantic segmentation classifies each pixel into categories (e.g., person, floor), but it does not track individuals or count zone entries over time.
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, count them in defined zones, and track their movement direction. Unlike general object detection, Spatial Analysis provides the specialized functions for zone occupancy and person trajectory tracking required by the retail scenario.
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 detect people in frames, but it does not track their movement across frames or count them entering/leaving specific zones.
✓
Spatial Analysis
Why this is correct
Spatial Analysis enables real-time analysis of people movement and occupancy in defined zones, making it ideal for this requirement.
Related concept
Read the scenario before looking for a memorised answer.
✗
Optical Character Recognition (OCR)
Why it's wrong here
OCR extracts text from images and is unrelated to detecting people or tracking movement.
✗
Semantic segmentation
Why it's wrong here
Semantic segmentation classifies each pixel into categories (e.g., person, floor), but it does not track individuals or count zone entries over time.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse object detection (which simply finds objects) with Spatial Analysis (which adds zone-aware tracking and counting), leading them to choose the more familiar 'Object detection' option without recognizing the need for directional tracking and zone occupancy.
Detailed technical explanation
How to think about this question
Spatial Analysis uses a combination of deep learning models and computer vision algorithms to detect persons in video frames, then applies tracking logic (e.g., Kalman filters) to follow each person across frames. It supports defining virtual zones (polygons) in the camera's field of view, and can trigger events when a person enters or exits a zone, as well as compute occupancy counts and directional vectors. In a real-world retail deployment, this enables heatmaps of foot traffic and dwell time analysis without requiring on-premises hardware, as it can run on Azure IoT Edge or in the cloud.
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, count them in defined zones, and track their movement direction. Unlike general object detection, Spatial Analysis provides the specialized functions for zone occupancy and person trajectory tracking required by the retail scenario.
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
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 →
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. 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?
medium
✓ A.Spatial Analysis
B.Object Detection
C.Image Classification
D.Optical Character Recognition (OCR)
Why A: 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.
Variation 2. 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?
hard
A.Image Classification
B.Optical Character Recognition (OCR)
C.Object Detection
✓ D.Spatial Analysis
Why D: 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.
Variation 3. A retail chain wants to analyze in-store security camera feeds to count the number of customers entering the store each hour. Which Azure Computer Vision capability should they use?
easy
A.Image classification
✓ B.Object detection
C.Optical Character Recognition (OCR)
D.Facial recognition
Why B: Object detection is the correct capability because it can identify and locate multiple instances of 'person' objects within each video frame, then track and count them over time to determine the number of customers entering per hour. Image classification only labels the entire image with a single category, which cannot provide per-object counts or spatial locations needed for accurate customer counting.
Variation 4. A retail store uses ceiling-mounted cameras to analyze customer traffic flow. They need to detect when a person enters a specific aisle and determine the direction they are walking. Which Azure Computer Vision capability should they use?
medium
A.Image Analysis dense captioning
B.Facial recognition
✓ C.People counting (Spatial Analysis)
D.Optical Character Recognition (OCR)
Why C: Option C is correct because Spatial Analysis, part of Azure Computer Vision, uses ceiling-mounted cameras to track people's movement and direction in a physical space. It specifically provides people counting and trajectory analysis, making it ideal for detecting when a person enters an aisle and determining their walking direction.
Variation 5. 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?
medium
A.Object detection
B.Optical character recognition (OCR)
✓ C.Spatial analysis
D.Image classification
Why C: 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.
Last reviewed: Jun 11, 2026
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.