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Implement computer vision solutionshardMultiple ChoiceObjective-mapped

AI-102 Implement computer vision solutions Practice Question

You have a real-time video processing pipeline using Azure AI Video Indexer. You need to detect when a specific person appears in archived video footage. Which approach minimizes latency and cost?

⚠ Common exam trap

Watch out — candidates often assume Custom Vision or Azure AI Face are needed for custom person detection, overlooking that Video Indexer already provides built-in face detection and search capabilities that are optimized for archived video analysis.

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

Use Video Indexer's face detection and indexing, then search

Video Indexer's built-in face detection and indexing automatically identifies and tracks faces during the indexing process, storing the results in a searchable metadata index. To detect when a specific person appears, you can then search the indexed metadata for that person's face ID or name, which avoids re-processing the video and minimizes both latency and cost. This approach leverages the one-time indexing cost and optimized search capabilities rather than running additional AI services on every frame.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Use Video Indexer's face detection and indexing, then search

    Why this is correct

    Video Indexer indexes faces efficiently and allows search without reprocessing.

  • Extract keyframes and use Custom Vision to detect the person

    Why it's wrong here

    Custom Vision requires training and may not be as efficient as Video Indexer's built-in face models.

  • Run face detection on every frame using Azure AI Face and store results

    Why it's wrong here

    Processing every frame is costly and high latency.

  • Use Azure AI Vision to detect faces in video frames and compare against a database

    Why it's wrong here

    This approach is custom and less efficient than Video Indexer's integrated solution.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This AI-102 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-102 exam.