I have ARKit or MediaPipe blendshape values and need FACS action units: what published mappings exist, how were they made, and which should I trust first?

Three mappings exist and are made differently: a practitioner ARKit table (Ozel), an expert-consensus MediaPipe-52 table (CNR clinical pre-proof, no validation against real facial behaviour data) and a learned AU-to-blendshape model (ICAT-EGVE 2024 poster). None was validated against manual FACS coding of the same footage, so any table is a hypothesis to check on your own clips; keep one-to-many cases (eyeSquint AU7 with AU44; cheekPuff AU33/AU34; jawOpen AU26/AU27) as multi-label. Curator qualifications: Texts read 2026-10-22; no mapping applied to footage, no model run. Clinical Supplementary Table S1 not read. Pre-proof licence gap per CA-B155. Curator amendment CA-AM-0048 (2026-10-22): Narrowed (curator, after C3R-0509). Ozel's 'cheekPuff AD34 - puff' is not a contradiction of the clinical panel. It corresponds to the panel's secondary AU34 (cheek puff, air trapped); the sources differ only in default primary (clinical AU33 cheek blow, with a blown-out vs trapped rule). The relation 'contradicts' is withdrawn and replaced by 'related (different default primary code)'. Two source-internal inconsistencies are added, and both are unresolved. First, the clinical pre-proof L1238 says only mouth shrug upper failed the threshold, while L1244 lists it among rows that technically reached consensus. Second, the EG poster's 9 x 100 x 4 = 3,600 does not match its 3,780 videos. Limitations: Texts read 2026-10-22; no mapping applied to footage, no model run. Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.

{
  "citations": [
    {
      "url": "https://iris.cnr.it/retrieve/b57d9fa2-3eb6-403b-8190-dbe4bbda0a16/Blendshape%20features%20meet%20action%20units%20pre-proof.pdf",
      "note": "melindaozel.com ARKit to FACS cheat sheet (curator readback), rows browDown..jawOpen, cheekPuff, mouthShrugUpper; CNR pre-proof (pdftotext) Results and Discussion; ICAT-EGVE 2024 poster egve20241392.pdf, abstract, dataset paragraph, Tables 1-2"
    },
    {
      "url": "https://diglib.eg.org/bitstreams/b0754f8b-5151-42c0-b3d4-89047e031724/download",
      "note": "melindaozel.com ARKit to FACS cheat sheet (curator readback), rows browDown..jawOpen, cheekPuff, mouthShrugUpper; CNR pre-proof (pdftotext) Results and Discussion; ICAT-EGVE 2024 poster egve20241392.pdf, abstract, dataset paragraph, Tables 1-2"
    },
    {
      "url": "https://melindaozel.com/arkit-to-facs-cheat-sheet/",
      "note": "melindaozel.com ARKit to FACS cheat sheet (curator readback), rows browDown..jawOpen, cheekPuff, mouthShrugUpper; CNR pre-proof (pdftotext) Results and Discussion; ICAT-EGVE 2024 poster egve20241392.pdf, abstract, dataset paragraph, Tables 1-2"
    }
  ]
}