Bali was chosen because the TRECVID DVU set ships character mugshots, but
its reference crops are unusable at scale: median detected face 27 px
against a 69 px maximum, so every reference was upscaled 4x or more past
what the embedder was trained for (AR-011). A 66 px floor left 2 of 69
references; no threshold exists that both keeps the faces in distribution
and leaves enough of them to calibrate.
SuperHero is 69 px median and 241 px max. Its gallery builds at a 66 px
floor with 14 references over 5 characters, and calibrates on its own
(a=15.2867 b=-4.98633, 100% train accuracy) instead of borrowing constants.
Measured on the fused 17-minute film, one stream rather than per-scene
clips so presence windows cross real scene boundaries as SR-002 intends:
precision 1.00, recall 0.65, F1 0.79 — 13 true positives, 0 false
positives, 7 misses. Every out-of-gallery character was declined rather
than forced onto a nearest match. The misses are the short scenes (14 s,
38 s, 27 s), consistent with per-track accumulation needing sightings.
- build_gallery gains --min-face-px, filtering the *detected face* rather
than the crop. The DVU images are scene crops, not mugshots, so crop
dimensions say nothing about face scale. A poisoned reference is
permanent in a way a bad frame is not: it corrupts every future match
against that identity.
- scripts/fetch_dvu.sh fetches mugshots, scene graphs and segmentation for
any DVU film. NIST names the same film three different ways, so KG_DIR
and KG_FILE are overridable rather than derived. This exists as a script
because the first copy of this data was assembled ad hoc in /tmp and was
lost with it, taking the working gallery along.
- Replay fixtures move to the artifact registry: push/pull_artifacts.sh
gain a replay-fixtures target, and tests/fixtures/dumps/.gitignore keeps
them out of git. superhero.h5 is ~9 MB and regenerating it needs the
film, the models and a GPU — none of which CI has. The gallery ships
with the dumps, since a dump only replays against the gallery it was
produced with.
- AR-012 and AR-013 coverage is ported onto the new fixture rather than
dropped with the Bali cases: 12369 assertions, up from 7991, since the
film is an order of magnitude larger than the clips.
Suite: 15679 assertions, 101 test cases.
TRACES: AR-011, AR-012, AR-013 | VR-001, VR-005 | SR-002
sae_audio exposes the shipped signature to Python. It compiles
audio_signature.cpp directly against FFmpeg rather than linking
sae_gallery: the signature needs no model, no OpenCV and no HDF5, so a
module that dragged those in would make `import sae_audio` depend on a
GPU-capable build of a path that is pure CPU DSP.
The point of binding rather than porting is that a fingerprint is only
useful if every implementation agrees byte for byte. A numpy port would
be a third implementation, and the one nobody checks against the golden
vector.
VR-014 then recovers a known trim from real film audio rather than from
the synthetic tone: 40 random in-cap offsets, every one recovered to the
nearest frame, worst error 46 ms against a 500 ms budget — and 46 ms is
the quantisation floor, not a result, since offsets land on whole
92.88 ms frames.
The soft spot is tier labelling rather than accuracy. Sub-frame
misalignment drags the score down (0.94-0.99 near a frame boundary,
0.69-0.73 at half a frame), demoting 27 of 40 correct alignments to
`loose`. Allowing +/-1 frame of slack in the score fixes it: all 40 back
to `audio` at min 0.906, false matches unmoved at 0.12-0.16, for 81 ms
of the budget.
The module stops at the producer's edge. Sliding one signature against
another is the consumer's algorithm (server SPEC §3, and the jRay
plugin implements it), so a caller writing that slide in numpy is not
duplicating anything this repo owns.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
TRACES: IR-004, IR-005 | VR-014 | UT-105, UT-106, UT-107, UT-108 | SR-003
dtourolle
