> For the complete documentation index, see [llms.txt](https://docs.unitlab.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.unitlab.ai/documentation/multimodal-annotations/multi-camera-video.md).

# Multi-camera video

Multi-camera work preserves event identity across viewpoints. The ontology and Instructions must state whether instances are view-local, event-level, or related across views.

![Multi-camera video layout](https://292810646-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FGjVLUz4wthGkGlRKM6rM%2Fuploads%2FuWV2FdAcECE2UrevUndn%2Fmultiview-video-workbench.png?alt=media\&token=77ad56ff-14dd-430b-9d53-cb23ba63956d)

*A stable camera order and synchronized navigation reduce view confusion during annotation and review.*

**Problem:** The same item appears in four camera views. Treating each recording as an independent task can create inconsistent identity and defect decisions.

**Unitlab pattern:**

1. Ingest the four camera files with consistent identifiers.
2. Use auto-grouping to create one Data Group per inspected item.
3. Arrange four video tiles in a custom layout.
4. Define object classes and defect properties in the ontology.
5. Use tracking or interpolation within each view.
6. Route uncertain cases to a specialist-configured Review stage.
7. Publish a release that preserves the grouped case.

This workflow keeps the four views connected from curation through release, so annotators can make one case-level decision with all relevant visual context available.

### Use this in production

* Define synchronization tolerance and the authoritative timestamp source.
* Name camera slots consistently and handle missing cameras explicitly.
* State how identity and properties relate across views.
* Review crossings, occlusion, and camera-specific blind spots across the full event.
* Confirm the release preserves group and camera-slot identity.