Realistic Representations of Cultural Heritage Sites and Objects through Laser Scanner Information
Bibliographic record
Abstract
When presenting the history of a heritage site or an artefact using multimedia technology, the proper use of technology to acquire and represent spatial information is crucial in order to facilitate the understanding of that particular site and the relationship between the elements constituting that site. In many cases, one has to model complex environments that have a rich historical content. These are composed of several objects with various characteristics and it is essential to combine data from different sensors and information from different sources. There is no single approach that works for all types of environment and at the same time is fully automated and satisfies the requirements of every application. A general approach combines information from historical material, multiple images, single images, laser scanner data, known shapes, CAD drawings, existing maps, survey data, and GPS data. This paper presents the work that was accomplished in preparing realistic representations of cultural heritage sites for interpretation and entertainment purposes. The general approach was applied to three cases: the Byzantine Crypt of Santa Cristina, Apulia; the remains of Temple C of Selinunte Sicily; a bronze sculpture with very fine incisions, and, a cave with Neolithic paintings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".