Pith Number

pith:RF7DILA7

pith:2026:RF7DILA7JOU6HXO4XE4OZA37AR

not attested not anchored not stored refs pending

Physics-Grounded Monocular Vehicle Distance Estimation Using Standardized License Plate Typography

Manognya Lokesh Reddy, Zheng Liu

Standardized US license plates serve as passive fiducial markers for accurate monocular vehicle distance estimation without training data.

arxiv:2604.12239 v2 · 2026-04-14 · cs.CV · eess.IV

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\usepackage{pith}
\pithnumber{RF7DILA7JOU6HXO4XE4OZA37AR}

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Record completeness

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Extensive outdoor experiments confirm a mean absolute error of 2.3% at 10 m and continuous distance output during brief plate occlusions, outperforming deep learning baselines by a factor of five in relative error.

C2weakest assumption

The standardized typography and dimensions of United States license plates can be reliably detected and measured as passive fiducial markers across the full range of automotive lighting and ambient conditions using the described four-method detector and three-stage identifier.

C3one line summary

A training-free monocular system uses US license plate typography and dimensions as fiducial markers to achieve 2.3% mean absolute error at 10 m for vehicle distance estimation via geometric priors and hybrid fusion.

Receipt and verification

First computed	2026-05-21T01:04:25.805930Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

897e342c1f4ba9e3dddcb938ec837f045d1e32cb8ca6ebc5389659b55d3649cc

Aliases

arxiv: 2604.12239 · arxiv_version: 2604.12239v2 · doi: 10.48550/arxiv.2604.12239 · pith_short_12: RF7DILA7JOU6 · pith_short_16: RF7DILA7JOU6HXO4 · pith_short_8: RF7DILA7

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/RF7DILA7JOU6HXO4XE4OZA37AR \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 897e342c1f4ba9e3dddcb938ec837f045d1e32cb8ca6ebc5389659b55d3649cc

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "8753603597788d1ec98a5e872523daf09e0a572c964ef00d034775dd46d0ae1c",
    "cross_cats_sorted": [
      "eess.IV"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-04-14T03:27:44Z",
    "title_canon_sha256": "48fdcfcaa09460e5e7f9900d4fca5bd8f34c305b59e40fa518b9138efdfaf512"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.12239",
    "kind": "arxiv",
    "version": 2
  }
}