AI-900 Practice Question: Describe features of computer vision workloads on Azure
What is 'video summarisation' in Azure Video Indexer and how does it work?
⚠ Common exam trap
Many candidates confuse 'video summarization' with 'transcript summarization' (Option A), because both involve summarization, but the key distinction is that video summarization outputs a video clip, not text.
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
✓
Automatically creating a highlight reel of the most informative video segments from a longer video
Video summarization in Azure Video Indexer automatically creates a highlight reel by selecting the most informative and visually interesting segments from a longer video. It uses AI models to analyze visual content, audio, and scene dynamics to identify key moments, such as changes in activity, faces, or objects, and then stitches these segments into a concise summary. This is distinct from transcript generation or chapter markers, as it focuses on extracting a condensed video output rather than text or navigation aids.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Generating a text transcript summary of what was said in the video
Why it's wrong here
Generating a text transcript summary applies natural language processing to the speech-to-text output, condensing what was said into a short written passage. This approach captures only the audio/verbal content and disregards visual cues, scene changes, and physical actions, which are essential for understanding video meaning. The output is a textual document, whereas video summarisation delivers a new, shorter video composed of selected original clips.
- ✓
Automatically creating a highlight reel of the most informative video segments from a longer video
Why this is correct
Video summarisation leverages computer vision and audio analysis to detect salient events, objects, faces, and speech patterns across a long recording, scoring each segment for informativeness or novelty. The AI then selects the highest-scoring clips and assembles them into a single, shortened highlight reel that preserves the essence of the original video. This output is a new edited video file, not just metadata or a transcript, and it is the core capability described by the term 'video summarisation' in Azure Video Indexer.
- ✗
Compressing video file size while maintaining acceptable visual quality
Why it's wrong here
Video compression reduces file size by re-encoding the footage with more efficient codecs (e.g., H.264/HEVC) and lowering bitrate, while preserving the full temporal and spatial content of the video. This is a media-encoding operation that does not understand semantics or select meaningful content. In contrast, video summarisation discards large portions of the original timeline and keeps only the most informative clips, fundamentally changing the content rather than merely shrinking the file.
- ✗
Adding automatic chapter markers and timestamps to a video for navigation
Why it's wrong here
Automatic chapter markers and timestamps are produced by Video Indexer's scene segmentation and topic detection, which identify transitions and label segments for navigation. They add a clickable timeline to the original video, but the video itself remains unmodified and full-length. Video summarisation, by contrast, generates a brand-new, shortened video composed of the best clips, so this option describes a supporting feature rather than the summarisation output.
Go deeper
Related to this question
About these practice questions
Courseiva writes every AI-900 question from scratch — 985 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.