video-analysis-pipeline

To generate Shorts from VODs, this pipeline analyzes long-form videos using a 14-signal fusion system to identify high-engagement moments. It then automatically extracts these highlights and organizes them into short-form clips suitable for YouTube Shorts.

Automated highlight detection works by applying a 14-signal fusion algorithm that evaluates audio, visual, and engagement metrics. This process identifies key moments in VOD content, isolating segments with high audience engagement and comedic timing for repurposing.

Yes, you need FFmpeg to process VOD files and extract clips. The pipeline requires FFmpeg for video analysis and processing, alongside the Claude API which provides content insights to determine the most engaging segments.

Yes, you can export generated clips to Premiere Pro. The pipeline supports multi-format export including Premiere Pro XMEML files, standard MP4 video, and JSON metadata, allowing seamless integration into existing professional editing workflows.

The best way to organize highlights is using the pipeline's automated clip pack generation, which categorizes detected video segments based on duration, platform, and theme. This structures the extracted shorts for efficient content publishing.

Processing long-form streams requires sufficient computational resources for FFmpeg analysis and Claude API usage. The pipeline relies on specific signal fusion algorithms to detect highlights, meaning streams lacking clear audio or visual engagement cues may yield fewer viable social media snippets.