Question 925 of 993
Implement computer vision solutionsmediumMultiple ChoiceObjective-mapped

AI-102 Implement computer vision solutions Practice Question

This AI-102 practice question tests your understanding of implement computer vision solutions. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.

Exhibit

{
  "version": "1.0",
  "recordings": [
    {
      "recordingId": "rec123",
      "sourceLanguage": "en-US",
      "targetLanguages": ["fr-FR", "de-DE"],
      "insightsToExtract": ["ocr", "faces", "labels"]
    }
  ]
}

Refer to the exhibit. You are configuring an Azure AI Video Indexer job. The exhibit shows a JSON snippet of the job configuration. What will Video Indexer extract from the video?

Exhibit

{
  "version": "1.0",
  "recordings": [
    {
      "recordingId": "rec123",
      "sourceLanguage": "en-US",
      "targetLanguages": ["fr-FR", "de-DE"],
      "insightsToExtract": ["ocr", "faces", "labels"]
    }
  ]
}

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

OCR text, detected faces, and visual labels

The JSON snippet configures an Azure Video Indexer job with the 'features' array set to include 'ocr', 'faces', and 'labels'. This instructs Video Indexer to extract OCR text (from on-screen text), detected faces (via facial detection and recognition), and visual labels (objects, scenes, and actions). These are the only features specified, so the output will contain exactly those three types of insights.

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.

  • OCR text, detected faces, and visual labels

    Why this is correct

    These are exactly the insightsToExtract specified.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Sentiment analysis of spoken content

    Why it's wrong here

    Sentiment is not listed in insightsToExtract.

  • Audio transcript and speaker diarization

    Why it's wrong here

    Not specified; would require 'transcript' or 'speakers'.

  • Keyframe extraction only

    Why it's wrong here

    Keyframes may be extracted by default, but not explicitly listed.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Azure AI Video Indexer candidates often confuse the effect of explicitly setting the 'features' array versus relying on default behavior. When features are explicitly listed, only those features are processed, overriding any defaults.

Detailed technical explanation

How to think about this question

Under the hood, Azure Video Indexer uses pre-built AI models for each feature: OCR leverages Azure Computer Vision's Read API for text extraction, face detection uses the Face API, and visual labels rely on the Computer Vision image analysis model. A subtle behavior is that if the 'features' array is omitted entirely, Video Indexer defaults to extracting all available insights, but when explicitly specified, only the listed features are processed, which can reduce cost and processing time. In a real-world scenario, a media company might use this to index archived videos for searchable text (OCR), identify celebrities (faces), and catalog scenes (labels) without incurring costs for audio transcription.

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.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this AI-102 question test?

Implement computer vision solutions — This question tests Implement computer vision solutions — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: OCR text, detected faces, and visual labels — The JSON snippet configures an Azure Video Indexer job with the 'features' array set to include 'ocr', 'faces', and 'labels'. This instructs Video Indexer to extract OCR text (from on-screen text), detected faces (via facial detection and recognition), and visual labels (objects, scenes, and actions). These are the only features specified, so the output will contain exactly those three types of insights.

What should I do if I get this AI-102 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: Jul 4, 2026

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