Question 262 of 1,020

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 does Azure AI Vision's 'people detection' (spatial analysis) feature track?

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

Counting, tracking movement, and measuring occupancy of people in defined zones from video

Azure AI Vision's spatial analysis (people detection) tracks the movement of people in video feeds, counting individuals and measuring how long they stay in defined zones. It does not identify specific people, detect masks or safety equipment, or measure body dimensions. This feature is designed for occupancy monitoring and flow analysis in physical spaces.

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.

  • Identifying the names of specific people in video footage

    Why it's wrong here

    Person identification (face recognition) is a different capability — spatial analysis detects and tracks anonymous people as counts/movements.

  • Counting, tracking movement, and measuring occupancy of people in defined zones from video

    Why this is correct

    Spatial analysis tracks anonymous people to measure occupancy, queue length, zone entry/exit, and dwell time.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Detecting whether people are wearing masks or safety equipment

    Why it's wrong here

    Safety equipment detection requires custom-trained models — spatial analysis tracks presence, count, and movement.

  • Measuring individual people's heights and body dimensions

    Why it's wrong here

    Biometric measurement requires specialized sensors — spatial analysis tracks presence and movement, not measurements.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates confuse 'people detection' with facial recognition or attribute detection (like masks), but Azure AI Vision's spatial analysis is strictly about anonymous tracking and counting, not identification or detailed attribute analysis.

Detailed technical explanation

How to think about this question

Spatial analysis uses computer vision models to detect bounding boxes for people in video frames, then tracks their centroids across frames using a Kalman filter-based tracker. It can count people entering or leaving a zone (e.g., a store aisle) and measure dwell time, but it does not persist any identity or biometric data. In real-world scenarios, this is used for retail analytics to optimize store layouts or for workplace safety to ensure social distancing without violating privacy.

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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

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: Counting, tracking movement, and measuring occupancy of people in defined zones from video — Azure AI Vision's spatial analysis (people detection) tracks the movement of people in video feeds, counting individuals and measuring how long they stay in defined zones. It does not identify specific people, detect masks or safety equipment, or measure body dimensions. This feature is designed for occupancy monitoring and flow analysis in physical spaces.

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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Last reviewed: Jun 11, 2026

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