Video indexing
Video indexing is the process of analyzing a video and building a structured, time-coded record of its contents, such as spoken words, on-screen text, objects, faces and scenes, so it can be searched quickly. Like the index at the back of a book, a video index tells software where each topic or item appears. Indexes are usually built when a video is uploaded.
Why it matters
An unindexed archive is effectively lost. Indexing makes years of footage reusable for new stories, clips and products. It also underpins search, moderation and recommendations, so its quality caps how well those features can work.
How it works
- When a video is uploaded, it is transcribed and analyzed for text, objects, faces and scenes.
- Each finding is recorded with the timestamp where it appears.
- The records are stored in a search index, and often as embeddings for meaning-based search.
- Queries look up the index and return videos plus the matching moments.
What is the difference between video indexing and video tagging?
Tagging attaches labels to a video, such as "cooking" or "interview." Indexing builds a full time-coded record of what appears and when, then stores it in a searchable structure. Tags are often one output of indexing. An index can tell you a phrase was spoken at 12:40, while a tag only says the topic exists.
How do I make old video archives searchable?
Run the archive through automated transcription and video analysis to build an index of words, text, faces and scenes with timestamps. Start with the most valuable collections, since processing costs grow with hours of footage. Add consistent metadata such as dates and locations, and store everything in a search system your editors already use. An archive project can be priced before it starts, since FastPix bills speech-to-text transcription at $0.048 per minute of footage.
Where it's used
News organizations index years of archive footage so it is searchable in seconds. Creator platforms rely on indexing for search and moderation, and SaaS products let users jump straight to the moment they need.
Where it usually goes wrong, and how FastPix handles it
Archives are often indexed with several separate tools, so transcripts, names and chapters end up in different places and drift away from the video they describe.
A transcript, chapters, a summary and named entities can be returned for each video stored in FastPix, through the API that also handles its upload and playback. Everything about a video stays in one place, so the index does not drift and editors can find archive footage when a story needs it.
