From pixel to mesh: accurate and straightforward 3D documentation of cultural heritage from the Cres/Lošinj archipelago

Most people like 3D visualizations. Whether it is in movies, holograms or games, 3D (literally) adds an extra dimension to conventional pictures. However, 3D data and their visualizations can also have scientic archaeological benets: they are crucial in removing relief distortions from photographs, facilitate the interpretation of an object or just support the aspiration to document archaeology as exhaustively as possible. Since archaeology is essentially a spatial discipline, the recording of the spatial data component is in most cases of the utmost importance to perform scientic archaeological research. For complex sites and precious artefacts, this can be a di€cult, time-consuming and very expensive operation. In this contribution, it is shown how a straightforward and cost-eective hard- and software combination is used to accurately document and inventory some of the cultural heritage of the Cres/Lošinj archipelago in three or four dimensions. First, standard photographs are acquired from the site or object under study. Secondly, the resulting image collection is processed with some recent advances in computer technology and so-called Structure from Motion (SfM) algorithms, which are known for their ability to reconstruct a sparse point cloud of scenes that were imaged by a series of overlapping photographs. When complemented by multi-view stereo matching algorithms, detailed 3D models can be built from such photo collections in a fully automated way. Moreover, the software packages implementing these tools are available for free or at very low-cost. Using a mixture of archaeological case studies, it will be shown that those computer vision applications produce excellent results from archaeological imagery with little eort needed. Besides serving the purpose of a pleasing 3D visualization for virtual display or publications, the 3D output additionally allows to extract accurate metric information about the archaeology under study (from single artefacts to entire landscapes)

Report on re3data COREF / CoreTrustSeal Workshop on Quality Management at Research Data Repositories

On October 5, 2022, the “Workshop on Quality Management at Research Data Repositories” – jointly organized by re3data COREF and CoreTrustSeal – was held online with more than 70 participants attending. The objective of the workshop was to discuss activities research data repositories perform to assure, assess, and improve data quality.The workshop started with input from the workshop organizers: re3data COREF presented results of a recent suvey on quality management at repositories, and CoreTrustSeal shared the perspective of a certification organization. Then, repositories from different disciplinary backgrounds presented their approaches to quality management. The workshop concluded with a breakout session and a plenary discussion on options for making information on data quality assurance more visible

Modelling building costs from 3D building models : estimating the construction effort from image-based surface models of dry-stone shepherd shelters (Kras, Slovenia)

In the second half of the 19th and early 20th century, sheep shepherds have built dry-stone shelters all over the Slovene Kras (or Karst) region. Despite being made out of stones that are interlocked without the use of any binding material, many of these vernacular constructions survived – even though sometimes only partially – the ravages of time. The fact that over one hundred fifty shepherd shelters are currently known is mainly due to the craftsmanship of their builders and thanks to (and even despite) their present location. A majority of these stone constructions can be found in areas that are nowadays forested, thus shielding them from weather-related or anthropogenic damage (because they are difficult to spot). This paper reports on the geometric documentation of those shelters using a photogrammetric computer vision pipeline, thereby mainly focussing on the difficulties that were encountered during this process. However, such image-based modelling approaches merely yield digital three-dimensional (3D) approximations of the shelters’ surface geometry (along with some sub-optimal colour data). Although these 3D surface models might be suitable to digitally preserve vulnerable vernacular buildings to some extent, they do not magically advance our understanding of them. The second part of this article focuses, therefore, on the extraction of archaeological information from these digital 3D constructions. More specifically, the total amount of stones, the total building time and the building cost regarding caloric energy expenditure are estimated for each of the digitised shelters. Although this assessment of architectural energetics provided useful insight into the building efforts and nutrient uptake of the shepherds, it also revealed many assumptions and shortcomings that often characterise archaeological information extraction from digital 3D models of buildings

Mind your grey tones. Examining the influence of decolourization methods on interest point extraction & matching for architectural image-based modelling

<p>This paper investigates the use of different greyscale conversion algorithms to decolourize colour images as input for two Structure-from-Motion (SfM) software packages. Although SfM software commonly works with a wide variety of frame imagery (old and new, colour and greyscale, airborne and terrestrial, large-and small scale), most programs internally convert the source imagery to single-band, greyscale images. This conversion is often assumed to have little, if any, impact on the final outcome. </p> <p>To verify this assumption, this article compares the output of an academic and a commercial SfM software package using seven different collections of architectural images. Besides the conventional 8-bit true-colour JPEG images with embedded sRGB colour profiles, for each of those datasets, 57 greyscale variants were computed with different colour-to-greyscale algorithms. The success rate of specific colour conversion approaches can, therefore, be compared with the commonly implemented colour-to-greyscale algorithms (luma Y’601, luma Y’709, or luminance CIE Y), both in terms of the applied feature extractor as well as of the specific image content (as exemplified by the two different feature descriptors and the various image collections, respectively).</p> <p><br> Although the differences can be small, the results clearly indicate that certain colour-to-greyscale conversion algorithms in an SfM-workflow constantly perform better than others. Overall, one of the best performing decolourization algorithms turns out to be a newly developed one.</p