Indexation d’objets 3D par spectre de formes géodésiques 3D (SFG3D)
Bibliographic record
Abstract
Dans ce papier, nous nous intéressons au problème d’indexation d’objets 3D par descripteurs de formes. L’approche proposée consiste à construire un nouveau descripteur intrinsèquement invariant aux transformations géométriques et robuste aux changements de topologie et au remaillage. Il s’agit de calculer au voisinage des points d’intérêts de la surface externe de la forme, le spectre de forme 3D (SF3D) retenu dans le standard MPEG-7 (Zaharia, 2001). Le voisinage autour de chaque point d’intérêt est obtenu par intersection des courbes de niveaux géodésiques et des lignes radiales. Les courbes de niveaux correspondent aux points situés à égales distances géodésiques du point d’intérêt. Les expériences effectuées sur les bases de test de SHREC’09 et de SHREC’11 montrent les propriétés du descripteur proposé et valident la pertinence de notre approche par rapport aux descripteurs proposés dans la littérature (Lian, 2009 ;2011).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".