Experience and Challenges in 3D Digital Documentation of Frescoed Walls and Ceilings from Images
Bibliographic record
Abstract
In this paper we report on our experience in creating photo-realistic virtual environments of frescoed surfaces to allow scientists, conservationists, historians, and tourists to closely study important frescoes at high level of details. In addition to allowing unlimited virtual access, this will also protect the frescoes from the damage that can be caused by opening the site to a large number of visitors. We address the main challenges associated with photo-realism or texture quality, and real-time interactive visualization and discuss available solutions. Where no effective solutions existed, we had to develop our own techniques. As case studies, we present results of modeling and visualization of two sites, both located at Buonconsiglio castle, one of the most important castles in Trentino in northern Italy. The first is the frescoed walls “Cycle of the Months”, a major masterpieces of international Gothic art that was painted around 1400. The second is the Gothic-Venetian Romanino loggia, named after the artist Girolamo Romanino (1484-1562) who decorated the ceiling and walls of the loggia, as well as the adjacent corridors, with remarkable frescoes in 1531.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".