Group the frames of one moment, by when they were taken and what they look like

A burst is the commonest thing in a cull and the least interesting: twelve
frames of the same gull at 10 fps occupy twelve cells, are scrolled past
twelve times, and end with the photographer keeping one. FR-CULL-5 asks for
them to collapse to one representative and be judged as a unit.

Two signals, because neither alone survives a real library. Time alone groups
a whole wedding ceremony -- a photographer working steadily never leaves the
gap that would end the run. Similarity alone groups a studio setup shot across
two days, which is a project rather than a moment. Together they are specific:
adjacent in time *and* looks like the frame before it.

Two seconds is the time bound, and the reason is worth recording because the
figure looks absurd next to a 10 fps camera. `images.captured_at` is whole
seconds -- EXIF's DateTimeOriginal has no sub-second field and
SubSecTimeOriginal is optional and widely omitted -- so a burst arrives in the
catalog as ten frames sharing one timestamp. Any threshold finer than a second
is a threshold on information that is not there. Where the pace really is
faster, the similarity bound is what separates the frames.

Similarity is a 64-bit difference hash over a 9x8 box-averaged reduction,
compared between *adjacent* frames only. Chained rather than anchored on the
first frame, because by frame twenty a camera following a bird has nothing in
common with frame one while no two neighbours differ by much; the time bound is
what stops the chain running away. There is no all-pairs step and there must
never be one -- that is what turns a grouping pass into something nobody can
afford to run over 50k images.

Nothing here ranks a frame. FR-CULL-5 names the failure it is avoiding, which
is rejecting the only frame of an important moment because somebody blinked, so
there is no sharpness score and no best-of-burst. The representative is the
earliest frame -- a fact about the clock, not a judgement about the photograph
-- and the user's own choice lives in its own table so that rebuilding the
grouping cannot erase it. Same argument `people.ignored` makes one subsystem
over: nothing short of remembering a decision survives re-clustering.

A newly found burst is recorded *open*. Collapsing on discovery would be
tidier, and would also mean a background pass taking photographs off the screen
part way through a cull. The pass marks; the user folds.

It is a pass rather than a job kind for the reason catalog.md 10.2 gives for
face clustering: a burst is a property of a run of frames and has no natural
subject_id, so a per-image job would rebuild the world once per photograph.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

core/dr-catalog/src/lib.rs

@@ -16,6 +16,7 @@
 //! - [`collections`] — the collection tree and membership the UI edits
 //! - [`keywords`] — the keyword vocabulary and what it is assigned to
 //! - [`faces`] — detected faces, the people they belong to, and who said so
+//! - [`bursts`] — frames that are one moment, grouped so they judge as one
 //! - [`jobs`] — the durable background work queue
 //! - [`trash`] — soft delete to a folder, then permanent delete
 //! - [`merge`] / [`sync`] — cross-device merging of collections and keywords
@@ -33,6 +34,7 @@ use std::path::Path;
 use dr_types::{Availability, ImageId};
 use rusqlite::Connection;
 
+pub mod bursts;
 pub mod cache;
 pub mod collections;
 pub mod dedup;