Scene understanding and model generation

Digital Twins and Enabling Technologies in Museums and Cultural Heritage: An Overview

“…Laser or drone scanning, remote sensing , LiDAR (light detection and ranging), 3D-imaging sensors, close- and midrange terrestrial laser scanning and structured light and multi-beam sensing [ 14 , 24 , 28 , 29 , 38 ] are used for image capturing, area mapping and identifying objects and their properties in five content-centric DTs.…”

“…It measures emitted or reflected radiation (in agriculture [ 2 ]), realizes inertial localization [ 5 , 19 ] or generates point clouds [ 14 , 28 ]. For 3D reconstruction in content-centric DTs, objects or artwork are scanned in their surroundings using camera [ 1 ], CCD (charge-coupled device) [ 9 ], laser [ 8 , 29 , 42 ], photogrammetry, triangulation in point clouds or other methods [ 9 , 14 , 24 , 38 , 40 ]. Such sensing for reconstruction occurs in seventeen content-centric-DTs.…”

“…Based on a reference corpus resulting from a search for scientific publications in books, journals and conference papers on the keywords virtual museums , digital twins , emerging technologies and sensor in leading science databases [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ], we classify DTs according to their application areas, relevant technologies and concepts depending on type, focus and features, sensor technology used and adaptation or innovation power throughout their life cycle. Design, realization, operation and evolution are guided by experts, engineers, customers, curators, software engineers and visitors, all of whom define adequate quality criteria (QC) and metrics (QM) for DTs and ViMs V&VA.…”

“…In this review paper, we examine prominent science databases for occurrences of the terms virtual, museum, digital, twin, emerging, technologies, and sensor in journals, book chapters, conference papers and ePublications. Recent searches in Scopus, IEEEXplore, and Google Scholar with the search string “virtual AND museum AND digital AND twin AND emerging AND technologies AND sensor” yield 43 relevant publications [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ] from the last 13 years, 34 of which were in Scopus, 3 of which were excluded because the keywords were used in other meanings, such as “Siamese twins” (cf. Figure 1 and Figure A1 in the Appendix A ).…”

CLOI-NET: Class segmentation of industrial facilities’ point cloud datasets

“…However, taking an example of a small petrochemical plant with 240,687 objects and 53,834 pipes, 2,382 manual labor hours are still needed to model these cylinders ). In summary, we have shown in (Agapaki and Brilakis 2020;Agapaki and Nahangi 2020) that the state-of-the-art 3D modeling practice has three main limitations: (a) the modelers fit standardized structural steel shapes after segmenting the structural elements manually or roughly selecting regions of interest using clipping polygons, (b) the modelers define parameters which determine cylinder detection and (c) EdgeWise does not directly assign class or instance labels per point. Rather it fits 3D solid standardized shapes and from them instance labels can be inferred.…”