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docs(decision): label the candidate-table figures as audit-time

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The F row's veto numbers were measured on v1 labels, which the audit itself
found to be 23% wrong. They are kept as the record of what was found, marked as
audit-time, and pointed at the current measurement rather than left to read as
present-day results. The OCR cost figure was re-measured: 18.0 ms/crop on 40
production-shaped crops, inside the recorded band.
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kiyo9w 2026-09-29 03:40:17 +09:00
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recognization/docs/research/2026-09-28-recognition-architecture/DECISION.md
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@ -208,10 +208,9 @@ Ordered by how much of the gap to a good product each class explains.
| D | Retrieval → Van's matcher | yes (DINO) | DINO recall collapses with scale (7/42 @10 at 493 SKUs) | DINO adds ~41 ms per crop | **Reject DINO retrieval.** |
| D′ | RootSIFT descriptor index (FLANN) → vote → verify top-10 | yes | 35–37/42, equal to or slightly better than exhaustive | 1.7–3.9 ms per crop flat from 7 to 493 SKUs; build 171 ms for 64k descriptors | **Adopt past ~150 SKUs.** |
| E | Retrieval → learned verifier | no | — | — | Only if C wins. |
| F | OCR text lane against catalog text signatures | yes (macOS Vision) | Veto: precision 62 → 82 % at τ=0.5 for −1 correct. As a lane: +10 correct at live, including unenrolled SKUs. | ~18–26 ms per crop on Mac; on-device on iOS (Vision) and Android (ML Kit) | **Adopt.** |
| F | OCR text lane against catalog text signatures | yes (macOS Vision) | Veto: precision 62 → 82 % at τ=0.5 for −1 correct. As a lane: +10 correct at live, including unenrolled SKUs. **Audit-time figures on v1 labels**; the current measurement is in § Re-measured 2026-09-29 (E-3): the lane adds 16 pp of coverage at full resolution while raising precision. | ~18–26 ms per crop on Mac (re-measured 18.0 ms on 40 production crops); on-device on iOS (Vision) and Android (ML Kit) | **Adopt.** |
| G | Fusion (geometry + colour + text + temporal + tag prior) | partly (geometry + colour + text) | Largest measured gain | — | **Adopt**; the text and geometry errors are complementary (text reads siblings apart; geometry covers text-poor faces). |
| H | Store-trained identity head on DINO | no (it was trained on the eval shelf) | Leaked; no valid measurement exists | — | Retire with DINO. |
| I | Barcode/JAN | — | Front faces rarely show JANs; shelf tags carry product text, not scannable codes, at scan distance | — | Only for the enrollment tool (scan a JAN, pull the packshot). |
| J | Shelf-tag / planogram prior | no (`tags.py` exists) | Every facing run on image6 sits above a readable tag with name and price | — | Strong hypothesis, H-02. |
## 5. Recommended architecture (current scale: tens of SKUs)