Question

A media company needs to build a workflow that ingests hour-long training videos and produces a structured JSON output containing a timeline of key topics discussed, per-segment natural-language summaries, and the timestamps where a presenter shows the screen versus faces the camera. The team wants to minimize custom model training and use a managed Azure capability that natively performs temporal analysis and generates grounded, multimodal descriptions of video content. Which approach should they use?

Accepted Answer

Use Azure AI Content Understanding with a video analyzer that produces segment-level fields, timestamps, and generated descriptions from a defined schema.

Answer

Extract frames at fixed intervals with FFmpeg and send each frame independently to an image captioning model, then concatenate the captions.

Answer

Use Azure AI Vision Image Analysis 4.0 with the caption and dense captions features on the full video file.

Answer

Train a custom object detection model in Azure AI Custom Vision to identify presenter poses across the video.