GigaMesh Software Framework

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GigaMesh Software Framework
Developer(s)since 2021: AG eHumanities & FCGLab, Institut for Computer Science, MLU Halle-Wittenberg
2009-2020 Forensic Computational Geometry Laboratory (FCGL),[1] IWR, Heidelberg University
Stable release
v.240221[2] / 21 February 2024; 2 months ago (2024-02-21)
Repositoryhttps://gitlab.com/fcgl/GigaMesh.git
Written inC++
Operating systemLinux, Windows 10
Available in1 languages
List of languages
English
TypeGraphics software
LicenseGNU General Public License
Websitehttps://gigamesh.eu

The GigaMesh Software Framework is a free and open-source software for display, editing and visualization of 3D-data typically acquired with structured light or structure from motion.[3]

It provides numerous functions for analysis of archaeological objects like cuneiform tablets, ceramics[4][5] or converted LiDAR data.[6] Typically applications are unwrappings (or rollouts),[7] profile cuts (or cross sections)[8] as well as visualizations of distances and curvature, which can be exported as raster graphics or vector graphics.

The retrieval of text in 3D like damaged cuneiform tablets or weathered medieval headstones[9] using Multi Scale Integral Invariant (MSII)[10] filtering is a core function of the software. Furthermore, small or faint surface details like fingerprints can be visualized.[11][12] The polygonal meshes of the 3D-models can be inspected, cleaned and repaired to provide optimal filtering results. The repaired datasets are suitable for 3D printing and for digital publishing in a dataverse.[13]

[edit]

The name "GigaMesh" refers to the processing of large 3D-datasets and relates intentionally to the mythical Sumerian king Gilgamesh and his heroic epic described on a set of clay tablets.[10]: 115  The central element of the logo is the cuneiform sign 𒆜 (kaskal) meaning street or road junction, which symbolizes the intersection of the humanities and computer science. The surrounding circle refers to the integral invariant computation using a spherical domain. The red color is derived from carmine, the color used by the Heidelberg University, where GigaMesh is developed.[citation needed]

Development and application in research projects[edit]

The development began in 2009 and was inspired by the edition project Keilschrifttexte aus Assur literarischen Inhalts (KAL, cuneiform texts with literary content) of the Heidelberg Academy of Sciences and Humanities.[11] In parallel it was applied within the Austrian Corpus Vasorum Antiquorum of the Austrian Academy of Sciences for documentation of red-figure pottery.[8] Current projects are funded by the DFG and the BMBF for contextualization and analysis of seals and sealings of the Corpus der minoischen und mykenischen Siegel,[14][15] where Thin Plate Splines are used for comparing sealings.[16] Analog to the developments for processing cuneiform tablets there are further approaches for adaption of the combined Computer Vision and Machine Learning methods for other Scripts in 3D. An example is the application within the Text Database and Dictionary of Classic Mayan.[17]

In 2017 GigaMesh was tested by the DAI at an excavation in Guadalupe, near Trujillo, Honduras for immediate visualization of in-situ acquired findings with different 3D-scanners including a comparison with manual drawings.[18] Since then GigaMesh is permanently used by the excavation team,[19] their feedback led to numerous changes to the GUI, improving the user experience (UX). Additionally online tutorials are published having a focus on tasks required to compile excavation reports.

The Scanning for Syria (SfS)[20] project of the Leiden University used GigaMesh in 2018 for 3D reconstruction of molds of tablets lost in ar-Raqqa, Syria based on Micro-CT-scans.[21][22] As a follow-up project the TU Delft acquired further Micro-CT-scans for virtually extracting clay tablets still wrapped into clay envelopes, which are unopened for thousands of years.[23][24] In May 2020 the SfS project won the European Union Prize for Cultural Heritage of the Europa Nostra in the category research.[25][26]

A first version (190416) for Windows was released in preparation for presentations about new functions shown at the international CAA 2019.[27]

The command line interface of GigaMesh is well suited to process large amounts of 3D-measurement data within repositories. This was demonstrated with almost 2.000 cuneiform tablets of the Hilprecht Collection of the Jena University, which were processed and digitally published as benchmarkdatabase (HeiCuBeDa)[28] for machine learning as well as database of images including 3D- and meta-data (HeiCu3Da)[29] using CC BY licenses.[30] A baseline for period classification of tablets was established using a Geometric Neural Network being a Convolutional Neural Network typically used for 3D-datasets.[31][32] In 2023, an extension of the dataset was published containing extracted images of cuneiform characters, cuneiform lines and individual annotated cuneiform characters. The annotations are made available together with the renderings with metadata as CSV and a knowledge graph (RDF). These developments were created in the context of the DFG project "Digital Edition of Cuneiform Texts from Haft Tappeh" in Mainz. The acronym MaiCuBeDa is derived from the project location.[33] This provided the first results for the localization of cuneiform characters and their wedges, which show that MSII rendering improves the recognition quality for photos.[34][35]

The Louvre showed GigaMesh based rollouts of an Aryballos from the collection of the KFU Graz representing the use of digital methods for research on pottery of ancient Greece within the CVA project, which had its 100th anniversary in 2019. Renderings of the rollouts were on display in the second half of 2019 in the display case named L’ère du numèrique et de l’imagerie scientifique (the digital era and scientific imaging).[36]

Version 191219 supports Texture maps common for 3D-data captured using photogrammetry. This allows processing and in particular unwrapping of objects acquired with Structure-from-Motion widely used for documentation of Cultural Heritage and in archaeology.[citation needed]

The Nara National Research Institute for Cultural Properties in Japan adapted GigaMesh for documentation and rollouts of vessels and published a tutorial,[37] which was used to implement the workflow for ceramics of the Jōmon period within the Togariishi Museum of Jōmon Archaeology.[38]

In April 2020 the source code was published on GitLab and the license changed from freeware to the GPL. Version 200529 allows for the first time to apply the MSII filter using the Graphical User Interface to visualize the smallest details like fingerprints.[39] The DFG funded edition of texts from Haft Tepe project[40] is using MSII filtered renderings of tablets in the so-called fat-cross arrangement of side views.[41]

GigaMesh is increasingly being used in areas that have methodological overlap with archaeology, such as geoengineering for the analysis of seashells.[42]

File formats and research data infrastructures[edit]

Primarily the Polygon File Format is supported and used to store additional information from the processing. This is not possible with the — additionally supported — Wavefront OBJ due to its specification. It is possible to export meshes in the glTF fileformat. The marking of interpolated points and triangles by filling voids in the triangular grid represents meta-information to be captured e.g. in the context of the National Research Data Infrastructure (NFDI) in Germany. Other metadata such as inventory numbers, material, and hyperlinks or Digital Object Identifiers (DOIs) can be captured. In addition, there is the ability to calculate topological metrics that describe the quality of a 3D measurement dataset.[43]

References[edit]

  1. ^ "FCGL: Forensic Computational Geometry Laboratory". fcgl.iwr.uni-heidelberg.de.
  2. ^ "Gigamesh". gigamesh.eu.
  3. ^ "An easy intro to 3D models from Structure from Motion (SFM, photogrammetry)". 2019-12-15. Retrieved 2020-04-10.
  4. ^ Thaller, Manfred (2014-09-18). "Are the Humanities an Endangered or a Dominant Species in the Digital Ecosystem?". Proceedings of the Third AIUCD Annual Conference on Humanities and Their Methods in the Digital Ecosystem. ACM. pp. 1–6. doi:10.1145/2802612.2802613. ISBN 9781450332958. S2CID 37289228.
  5. ^ Pintus, Ruggero; Pal, Kazim; Yang, Ying; Weyrich, Tim; Gobbetti, Enrico; Rushmeier, Holly (2015-08-06). "A Survey of Geometric Analysis in Cultural Heritage". Computer Graphics Forum. 35 (1): 4–31. CiteSeerX 10.1.1.722.6692. doi:10.1111/cgf.12668. ISSN 0167-7055. S2CID 6558660.
  6. ^ Hämmerle, Martin; Höfle, Bernhard (2017-12-05), "Introduction to LiDAR in Geoarchaeology from a Technological Perspective", Digital Geoarchaeology, Natural Science in Archaeology, Springer International Publishing, pp. 167–182, doi:10.1007/978-3-319-25316-9_11, ISBN 9783319253145
  7. ^ Bayer, Paul; Lamm, Susanne (2018), Trinkl, Elisabeth (ed.), "Mehr als nur Ben Hur – Eine 3D-Abrollung des römischen Silberbecher von Grünau", Forum Archaeologiae (in German), vol. 87, no. VI, ISSN 1605-4636
  8. ^ a b Mara, Hubert; Portl, Julia (2013), Trinkl, Elisabeth (ed.), "Acquisition and Documentation of Vessels using High-Resolution 3D-Scanners" (PDF), Corpus Vasorum Antiquorum Österreich, vol. Beiheft 1, Verlag der Österreichischen Akademie der Wissenschaften — VÖAW, pp. 25–40, ISBN 978-3-7001-7145-4, retrieved 2018-08-24, KBytes: 900
  9. ^ Kurt F. de Swaaf (2010-06-30), "Gemeißelte Geheimnisse: Forscher entziffern jüdische Grabinschriften", Spiegel Online (in German), retrieved 2018-08-03
  10. ^ a b Hubert Mara (2012), Multi-Scale Integral Invariants for Robust Character Extraction from Irregular Polygon Mesh Data, Heidelberg: Heidelberg University Library, doi:10.11588/heidok.00013890
  11. ^ a b Mara, Hubert; Krömker, Susanne; Jakob, Stefan; Breuckmann, Bernd (2010), "GigaMesh and Gilgamesh — 3D Multiscale Integral Invariant Cuneiform Character Extraction", Proceedings of VAST International Symposium on Virtual Reality, Archaeology and Cultural Heritage, Palais du Louvre, Paris, France: Eurographics Association, pp. 131–138, doi:10.2312/VAST/VAST10/131-138, ISBN 9783905674293, ISSN 1811-864X, retrieved 2019-06-23
  12. ^ Hubert Mara (2017), Visual Computing for Analysis of Sealings, Script and Fingerprints in 3D, Presentation about Multi Scale Integral Invariant filtering with illustrating images (PDF), archived from the original (PDF) on 2018-08-02, retrieved 2018-08-24, KBytes: 8700
  13. ^ heiDATA — IWR Computer Graphics Dataverse in der Universitätsbibliothek Heidelberg
  14. ^ "DFG - GEPRIS - Minoische Siegelglyptik zwischen corpusartiger Erfassung und 3D-Forensik. Eine multidisziplinäre Dokumentation von 900 unpublizierten Siegeln aus dem Archäologischen Museum von Heraklion" (in German). Retrieved 2018-09-11.
  15. ^ "ErKon3D — Erschließung und Kontextualisierung von ägäischen Siegeln und Siegelabdrücken mit 3D-Forensik" [3D forensic analysis and contextualisation of aegean seals and sealings]. funding portal of the German federal government (in German). Retrieved 2020-09-07. "ErKon3D short description". portal for scientific collections (in German). Retrieved 2020-09-07.
  16. ^ Bogacz, Bartosz; Papadimitriou, Nikolas; Panagiotopoulos, Diamantis; Mara, Hubert (2019), "Recovering and Visualizing Deformation in 3D Aegean Sealings", Proc. of the 14th International Conference on Computer Vision Theory and Application (VISAPP), Prague, Czech Republic, retrieved 28 March 2019
  17. ^ Feldmann, Felix; Bogacz, Bartosz; Prager, Christian; Mara, Hubert (2018), "Histogram of Oriented Gradients for Maya Glyph Retrieval", Proc. of the 16thEurographics Workshop on Graphics and Cultural Heritage (GCH), Vienna, Austria: The Eurographics Association, pp. 105–111, doi:10.2312/gch.20181346, ISBN 978-3-03868-057-4, ISSN 2312-6124, retrieved 2020-02-03
  18. ^ Reindel, Markus; Fux, Peter; Fecher, Franziska (2018), "Archäologisches Projekt Guadalupe: Bericht über die Feldkampagne 2017", Jahresberichte (in German), vol. 2017, Zürich, Switzerland: SLSA, Schweizerisch-Liechtensteinische Stiftung für archäologische Forschungen im Ausland, doi:10.5167/uzh-158145
  19. ^ Fecher, Franziska; Reindel, Markus; Fux, Peter; Gubler, Brigitte; Mara, Hubert; Bayer, Paul; Lyons, Mike (2020), Burkhard Vogt und Jörg Linstädter (ed.), "The ceramic finds from Guadalupe, Honduras: Optimizing archaeological documentation with a combination of digital and analog techniques", Journal of Global Archaeology (JOGA), Bonn, Germany: Deutsches Archäologisches Institut, Kommission für Archäologie Aussereuropäischer Kulturen, pp. § 1–54–§ 1–54, doi:10.34780/joga.v2020i0.1009, ISSN 2701-5572
  20. ^ "Website of the Scanning for Syria project at the Leiden University". Retrieved 2019-11-27.
  21. ^ Ngan-Tillard, Dominique (2018-06-05), Scanning for Syria - digital book of cuneiform tablet T98-34, Delft, Netherlands, doi:10.4121/uuid:0bd4470b-a055-4ebd-b419-a900d3163c8a, retrieved 2020-02-03{{citation}}: CS1 maint: location missing publisher (link)[permanent dead link], KBytes: 48600
  22. ^ Nieuwenhuyse, Olivier; Hiatlih, Khaled; al-Fakhri, Ayham; Haqi, Rasha; Ngan-Tillard, Dominique; Mara, Hubert; Burch Joosten, Katrina (2019), "Focus Raqqa: Schutz für das archäologische Erbe des Museums von ar-Raqqa", Antike Welt (in German), wbg Philipp von Zabern, pp. 76–83, retrieved 2019-12-17[permanent dead link]
  23. ^ Seeing through clay: 4000 year old tablets in hypermodern scanner on YouTube
  24. ^ Unpacking a Cuneiform Tablet wrapped in a clay envelope on YouTube, cf. doi:10.11588/heidok.00026892
  25. ^ "Website of the Europa Nostra Award for the Scanning for Syria project". Retrieved 2020-05-07.
  26. ^ "Website of the Scanning for Syria project by the Leiden-Delft-Erasmus Centre for Global Heritage and Development". 7 May 2020. Retrieved 2020-07-03.
  27. ^ "International Conference on Computer Applications and Quantitive Methods in Archaeology, Krakau, Poland, 2019". Retrieved 2019-04-16.
  28. ^ Mara, Hubert (2019-06-06), HeiCuBeDa Hilprecht – Heidelberg Cuneiform Benchmark Dataset for the Hilprecht Collection, heiDATA – institutional repository for research data of Heidelberg University, doi:10.11588/data/IE8CCN
  29. ^ Mara, Hubert (2019-06-06), HeiCu3Da Hilprecht – Heidelberg Cuneiform 3D Database - Hilprecht Collection, heidICON – Die Heidelberger Objekt- und Multimediadatenbank, doi:10.11588/heidicon.hilprecht
  30. ^ Mara, Hubert; Bogacz, Bartosz (2019), "Breaking the Code on Broken Tablets: The Learning Challenge for Annotated Cuneiform Script in Normalized 2D and 3D Datasets", Proceedings of the 15th International Conference on Document Analysis and Recognition (ICDAR), Sydney, Australia, pp. 148–153, doi:10.1109/ICDAR.2019.00032, ISBN 978-1-7281-3014-9, S2CID 211026941
  31. ^ Bogacz, Bartosz; Mara, Hubert (2020), "Period Classification of 3D Cuneiform Tablets with Geometric Neural Networks", Proceedings of the 17th International Conference on Frontiers of Handwriting Recognition (ICFHR), Dortmund, Germany, pp. 246–251, doi:10.1109/ICFHR2020.2020.00053, ISBN 978-1-7281-9966-5, S2CID 227219798
  32. ^ Presentation of the ICFHR paper on Period Classification of 3D Cuneiform Tablets with Geometric Neural Networks on YouTube
  33. ^ Hubert Mara, Timo Homburg (2023-08-29), MaiCuBeDa Hilprecht – Mainz Cuneiform Benchmark Dataset for the Hilprecht Collection, heiDATA – institutional repository for research data of Heidelberg University, doi:10.11588/data/QSNIQ2
  34. ^ Ernst Stötzner, Timo Homburg, Jan Philipp Bullenkamp and Hubert Mara (2023), "R-CNN based PolygonalWedge Detection Learned from Annotated 3D Renderings and Mapped Photographs of Open Data Cuneiform Tablets", Proceedings of the 21th Eurographics Workshop on Graphics and Cultural Heritage (GCH), Salento, Italy, pp. 47–56, doi:10.2312/gch.20231157, ISBN 9783038682172, ISSN 2312-6124, retrieved 2023-11-06{{citation}}: CS1 maint: multiple names: authors list (link)
  35. ^ Stötzner, Ernst; Homburg, Timo; Mara, Hubert (2023), "CNN based Cuneiform Sign Detection Learned from Annotated 3D Renderings and Mapped Photographs with Illumination Augmentation", Proceedings of the International Conference on Computer Vision (ICCV), Paris, France, pp. 1672–1680, arXiv:2308.11277, doi:10.1109/ICCVW60793.2023.00183, ISBN 979-8-3503-0744-3
  36. ^ "IWR Newsroom, Contribution of visualizations to an archaeological Exhibition in the Louvre Museum". 2019-07-13. Retrieved 2020-01-31.
  37. ^ "文化財の壺 第7号 特集:文化財研究を進める技術を考える, Issue 7, June 2019, ISBN 21851972" (in Japanese). Retrieved 2020-04-10.
  38. ^ Araki Minoru (2020-01-30). "Blog entry about rollouts of Jōmon period vessels in Nara" (in Japanese). Retrieved 2021-10-04. "Rollout tutorial" (in Japanese). 2021-09-30. Retrieved 2021-10-04.
  39. ^ MSII Filtering: Cuneiform Characters & Fingerprints on YouTube
  40. ^ "DFG - GEPRIS - Digitale Edition der Keilschrifttexte aus Haft Tappeh (Iran)" (in German). Retrieved 2021-01-17.
  41. ^ Brandes, Tim; Huber, Eva-Maria (2020), Behzad Mofidi-Nasrabadi (ed.), "Die Texte aus Haft Tappeh – Beobachtungen zu den Textfunden aus Areal I", Elamica: Contributions on History and Culture of Elam and Its Neighbouring Regions (in German), no. 10, Hildesheim, Germany: Franzbecker, pp. 9–42, ISBN 978-3881208802
  42. ^ Zhao, Yumeng; Deng, Bozhi; Cortes, Douglas D.; Dai, Sheng (2023), "Morphological Advantages of Angelwing Shells in Mechanical Boring", Acta Geotechnica, Springer, doi:10.1007/s11440-023-01962-w, S2CID 259731305
  43. ^ Homburg, Timo; Cramer, Anja; Raddatz, Laura; Mara, Hubert (2021), "Metadata Schema and Ontology for Capturing and Processing of 3D Cultural Heritage Objects", Heritage Science, vol. 9, no. 91, Springer, doi:10.1186/s40494-021-00561-w, S2CID 236438045

External links[edit]

  • GigaMesh.eu - website of the GigaMesh Software Frameworks including tutorials, publications and downloads
  • ResearchGate - additional project website and blog
  • Cuneur - Keilschrift beschriften an annotation tool for cuneiform tablets represented by renderings, images stacks and photographs