Smart grouping

Burst shots of the same animal collapse into one tidy event.

A single animal walking past a camera rarely triggers one photo — it triggers a burst of ten or twenty, seconds apart. Reviewed frame by frame, that's a flood. Smart grouping collapses each burst into a single, tidy event. This grouped timeline — series view — is how TrailCamHub shows your library by default.

How frames become an event

Photos captured close together in time on the same camera are recognised as one trigger and grouped automatically. Instead of twenty near-identical thumbnails, you see one event with the best frames inside it.

Made coherent by recognition

Because every frame has already been analysed, the event arrives labelled: which species is present, how many animals, whether a person or vehicle was involved. A burst of a browsing roe deer becomes "Roe deer — 1 animal," not a wall of pictures you have to interpret. When the frames agree on species and count, the event is shown with confidence; when they disagree, that's surfaced for a quick look.

Why it matters

Trail-camera libraries balloon precisely because of bursts. Grouping them is the difference between scrolling for an hour and skimming a clean timeline of visits. Each event becomes one decision — keep, tag, share or discard — instead of twenty.

Prefer the raw frames?

Series view is the default, but you're not locked into it. Switch to image view anytime to turn grouping off and browse every individual photo one by one — nothing is deleted or changed, you simply see the ungrouped frames. Flip between the two whenever it suits the task.

A note on how it works: grouping is based on capture time and camera, enriched by the AI's species and counts. It organises a visit into one entry rather than visually re-identifying the specific individual across frames — but the result reads the same either way: your library becomes events, not raw frames.