The answer is Azure AI Video Indexer, the correct choice because it is specifically designed for video analysis, using AI-powered computer vision to detect, track, and identify people or objects across frames over time. This capability relies on object tracking algorithms and face detection that follow movement frame by frame, enabling you to pinpoint when and where a person or item appears in a video. On the Microsoft Azure AI Fundamentals AI-900 exam, this tests your understanding of which Azure service handles video-based insights, often appearing as a scenario where you need to distinguish Video Indexer from Computer Vision (which analyzes still images) or Custom Vision (which trains on static pictures). A common trap is confusing Video Indexer with Azure Video Analyzer for Media, but remember that Video Indexer is the newer, unified name for the same service. Memory tip: think “Video Indexer tracks across frames” — the word “across” reminds you it follows movement over time, not just a single snapshot.
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.
Which Azure AI capability can analyze video to identify and track specific people or objects across frames?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure AI Video Indexer
Azure AI Video Indexer is the correct choice because it is specifically designed to analyze video content, including the ability to detect, track, and identify people or objects across frames using AI-powered computer vision and audio analysis. It provides features like face detection, object tracking, and motion detection over time, making it suitable for this 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.
✗
Azure AI Custom Vision
Why it's wrong here
Custom Vision processes individual images — it doesn't provide video analysis with temporal tracking.
✓
Azure AI Video Indexer
Why this is correct
Video Indexer analyzes video content using AI, providing face identification, object tracking, scene detection, and automatic transcription.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure AI Face
Why it's wrong here
Azure AI Face detects faces in individual images — Video Indexer provides comprehensive video-level analysis.
✗
Azure AI Vision OCR
Why it's wrong here
OCR extracts text from images — Video Indexer provides comprehensive video content analysis.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure AI Video Indexer with Azure AI Custom Vision or Azure AI Face, mistakenly thinking that image-based services can handle video analysis, but Video Indexer is the only option that natively supports temporal tracking across video frames.
Detailed technical explanation
How to think about this question
Azure AI Video Indexer uses a combination of pre-built AI models, including object detection (e.g., YOLO-based models) and face recognition, to process video frames sequentially and maintain object identities across frames via tracking algorithms like Kalman filters or optical flow. In a real-world scenario, it can be used to analyze security footage to count people entering a building, track a specific vehicle across multiple camera angles, or detect unusual object movements in retail analytics.
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: Azure AI Video Indexer — Azure AI Video Indexer is the correct choice because it is specifically designed to analyze video content, including the ability to detect, track, and identify people or objects across frames using AI-powered computer vision and audio analysis. It provides features like face detection, object tracking, and motion detection over time, making it suitable for this 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.
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Question Discussion
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