Automatic indexation of Cultural Heritage 3D object

• Autorzy: Le-Tien Mau , Nguyen-Thanh Khoi , Raffin Romain

Identyfikatory

DOI

10.7494/csci.2025.26.1.5288

• Języki publikacji: EN

Abstrakty

EN

There has been significant evolution in the fields of 3D digitization thanks tothe development of 3D reconstruction and geometry processing. The resultsof digitization researches have been widely applied in many fields, especiallyin Cultural Heritage and Archaeology. Reconstruction, characterization andannotation of components forming 3D objects have become an effective tool forresearch, conservation and promotion of archaeological relics. The aim of thispaper is to propose a process of 3D model reconstruction, segmentation andannotation on the basis of a enhanced corresponding 2D dataset. A machinelearning method is used for the semantic segmentation of 2D images, therebylabel, annotate and reconstruct a 3D model based upon links between distinctive invariant features, orientation of images, and depth map of images. Theinitial result as a data basis for research, reconstruction and identification ofparts in 3D objects is applied in the reconstruction of archaeological relics, object identification, 3D printing, etc. Our work uses the data collected from theMuseum of Cham Sculpture DaNang and the Myson QuangNam sanctuary inVietNam, to carry out the proposed method.

Słowa kluczowe

EN

3D reconstruction; cultural heritage; semantic annotation; 3D digitization

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Science
• Rocznik: 2025
• Tom: T. 26 (1)
• Strony: 5--25
• Opis fizyczny: Bibliogr. 26 poz., rys., wykr.

Twórcy

autor

Le-Tien Mau

• Danang University of Science and Technology, Vietnam

autor

Nguyen-Thanh Khoi

• Danang University of Science and Technology, Vietnam

autor

Raffin Romain

• University of Burgundy, LIB, France

Bibliografia

• [1] Adam A., Chatzilari E., Nikolopoulos S., Kompatsiaris I.: H-RANSAC: A hy-brid point cloud segmentation combining 2D and 3D data,ISPRS Annals of thePhotogrammetry, Remote Sensing and Spatial Information Sciences, vol. IV-2,pp. 1–8, 2018. doi: 10.5194/isprs-annals-iv-2-1-2018.
• [2] Belhi A., Foufou S., Bouras A., Sadka A.H.: Digitization and Preservation of Cul-tural Heritage Products. In: J. Ríos, A. Bernard, A. Bouras, S. Foufou (eds.), Product Lifecycle Management and the Industry of the Future, pp. 241–253,Springer, Cham, 2017. doi: 10.1007/978-3-319-72905-3_22.
• [3] El-Hakim S.F., Beraldin J.-A., Picard M., Godin G.: Detailed 3D reconstructionof large-scale heritage sites with integrated techniques, IEEE Computer Graphicsand Applications, vol. 24(3), pp. 21–29, 2004. doi: 10.1109/MCG.2004.1318815.
• [4] Grilli E., Dininno D., Petrucci G., Remondino F.: From 2D to 3D supervisedsegmentation and classification for cultural heritage applications,ISPRS – International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLII-2, pp. 399–406, 2018. doi: 10.5194/isprs-archives-XLII-2-399-2018.
• [5] He K., Gkioxari G., Dollár P., Girshick R.: Mask R-CNN,2017 IEEE International Conference on Computer Vision (ICCV), 2017. doi: 10.1109/iccv.2017.322.
• [6] Hubert J.-F.:The art of Champa, Parkstone International, 2011.
• [7] Le-Tien M., Nguyen-Tan K., Raffin R.: Matching correspondence between imagesand 3D model in a reconstruction process,Journal of Science and Technology:Issue on Information and Communications Technology, vol. 2(1), pp. 64–69, 2016.doi: 10.31130/jst.2016.29.
• [8] Le-Tien M., Nguyen-Tan K., Raffin R.: A Method to Determine the Characteristic of Object Based on 2D/3D Correspondence. In:2019 IEEE-RIVF International Conference on Computing and Communication Technologies (RIVF),2019. doi: 10.1109/RIVF.2019.8713732.
• [9] Lin T.Y., Maire M., Belongie S., Bourdev L., Girshick R., Hays J., Perona P.,et al.: Microsoft COCO: Common Objects in Context, CoRR, vol. abs/1405.0312,2015. doi: 10.48550/arXiv.1405.0312.
• [10] Lowe D.G.: Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, vol. 60(2), pp. 91–110, 2004. doi: 10.1023/B:VISI.0000029664.99615.94.
• [11] Manuel A., Gattet E., De Luca L., Véron P.: An approach for precise 2D/3Dsemantic annotation of spatially-oriented images for in situ visualization applications. In: 2013 Digital Heritage International Congress (DigitalHeritage), vol. 1, pp. 289–296, 2013. doi: 10.1109/DigitalHeritage.2013.6743752.
• [12] Manuel A., M’Darhri A.A., Abergel V., Rozar F., De Luca L.: A semi-automatic 2D/3D annotation framework for the geometric analysis of heritage artefacts. In:2018 3rd Digital Heritage International Congress (DigitalHERITAGE) heldjointly with 2018 24th International Conference on Virtual Systems&Multimedia(VSMM 2018), pp. 1–7, 2018. doi: 10.1109/DigitalHeritage.2018.8810114.
• [13] Manuel A., Véron P., De Luca L.: 2D/3D Semantic Annotation of Spatialized Images for the Documentation and Analysis of Cultural Heritage. In: C.E. Catalano, L. De Luca (eds.),14th EUROGRAPHICS Workshop on Graphics and Cultural Heritage, Eurographics, Genova, Italy, 2016. doi: 10.2312/gch20161391.
• [14] Noh Z., Sunar M.S., Pan Z.: A Review on Augmented Reality for Virtual Heritage System. In: Learning by Playing. Game-based Education System Design and Development, vol. 5670, pp. 50–61, 2009. doi: 10.1007/978-3-642-03364-3_7.
• [15] Özyeşil O., Voroninski V., Basri R., Singer A.: A survey of structure from motion, CoRR, vol. abs/1701.08493, 2017. doi: 10.1017/s096249291700006x.
• [16] Pierrot-Deseilligny M.: Micmac Interface, http://logiciels.ign.fr/IMG/pdf/docinterface.en.pdf.
• [17] Pierrot-Deseilligny M., Clery I.: Apero, An Open Source Bundle Adjusment Software for Automatic Calibration and Orientation of Set of Images, ISPRS– International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVIII-5/W16, pp. 269–276, 2011. doi: 10.5194/isprsarchives-XXXVIII-5-W16-269-2011.
• [18] Pierrot-Deseilligny M., De Luca L., Remondino F.: Automated Image-Based Procedures for Accurate Artifacts 3D Modeling and Orthoimage Generation, Geoinformatics FCE CTU, vol. 6, pp. 291–299, 2011. doi: 10.14311/gi.6.36.
• [19] Pierrot-Deseilligny M., Jouin D., Belvaux J., Maillet G., Girod L., Rupnik E.,Muller J., et al.: Micmac, apero, pastis and other beverages in a nutshell, Institut Géographique National, 2014.
• [20] Remondino F.: Heritage Recording and 3D Modeling with Photogrammetry and 3D Scanning, Remote Sensing, vol. 3, pp. 1104–1138, 2011. doi: 10.3390/rs3061104.
• [21] Remondino F., El-Hakim S., Girardi S., Rizzi A., Benedetti S., Gonzo L.: 3D Virtual Reconstruction and Visualization of Complex Architectures – The“3D-ARCH” Project, International Archives of the Photogrammetry, RemoteSensing and Spatial Information Sciences, vol. 38, 2009.
• [22] Ren S., He K., Girshick R., Sun J.: Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39(6), pp. 1137–1149, 2017. doi: 10.1109/TPAMI.2016.2577031.
• [23] Roy S., Cox I.J.: A maximum-flow formulation of the N-camera stereo correspondence problem. In: Sixth International Conference on Computer Vision (IEEECat. No.98CH36271), pp. 492–499, 1998. doi: 10.1109/ICCV.1998.710763.
• [24] Rupnik E., Daakir M., Pierrot-Deseilligny M.: MicMac – a free, open-source solution for photogrammetry, Open Geospatial Data, Software and Standards,vol. 2, pp. 1–9, 2017. doi: 10.1186/s40965-017-0027-2.
• [25] Stathopoulou E.K., Remondino F.: Multi view stereo with semantic priors, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLII-2/W15, pp. 1135–1140, 2019. doi: 10.5194/isprs-archives-xlii-2-w15-1135-2019.
• [26] Xiong J., Heidrich W.: In-the-Wild Single Camera 3D Reconstruction Through Moving Water Surfaces. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 12558–12567, 2021. doi: 10.1109/iccv48922.2021.01233.