Reference : 3D Point Clouds in Archaeology: Advances in Acquisition, Processing and Knowledge Int...
Scientific journals : Article
Engineering, computing & technology : Computer science
Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
http://hdl.handle.net/2268/214931
3D Point Clouds in Archaeology: Advances in Acquisition, Processing and Knowledge Integration Applied to Quasi-Planar Objects
English
[fr] Nuages de points 3D en archéologie: Avancées dans l'acquisition, le traitement et l'intégration de connaissances appliquées aux objets quasi-planaires
Poux, Florent mailto [Université de Liège - ULiège > Département de géographie > Unité de Géomatique - Topographie et géométrologie >]
Neuville, Romain mailto [Université de Liège - ULiège > Département de géographie > Unité de Géomatique - Topographie et géométrologie >]
Van Wersch, Line mailto [Université de Liège - ULiège > Département des sciences historiques > Archéologie médiévale et post-médiévale >]
Nys, Gilles-Antoine mailto [Université de Liège - ULiège > Département de géographie > Unité de Géomatique - Topographie et géométrologie >]
Billen, Roland mailto [Université de Liège - ULiège > Département de géographie > Unité de Géomatique - Topographie et géométrologie >]
30-Sep-2017
Geosciences
MDPI
7
4
Special Issue Remote Sensing and Geosciences for Archaeology
96
Yes (verified by ORBi)
International
2076-3263
Basel
Suisse
[en] point cloud ; data fusion ; laser scanning ; dense image-matching ; feature extraction ; classification ; knowledge integration ; cultural heritage ; ontology
[fr] Nuage de points ; Fusion de données ; Scanner laser ; corrélation d'images dense ; extraction de caractéristiques ; classification ; intégration de connaissances ; conservation du patrimoine ; ontologie
[en] Digital investigations of the real world through point clouds and derivatives are changing how curators, cultural heritage researchers and archaeologists work and collaborate. To progressively aggregate expertise and enhance the working proficiency of all professionals, virtual reconstructions demand adapted tools to facilitate knowledge dissemination. However, to achieve this perceptive level, a point cloud must be semantically rich, retaining relevant information for the end user. In this paper, we review the state of the art of point cloud integration within archaeological applications, giving an overview of 3D technologies for heritage, digital exploitation and case studies showing the assimilation status within 3D GIS. Identified issues and new perspectives are addressed through a knowledge-based point cloud processing framework for multi-sensory data, and illustrated on mosaics and quasi-planar objects. A new acquisition, pre-processing, segmentation and ontology-based classification method on hybrid point clouds from both terrestrial laser scanning and dense image matching is proposed to enable reasoning for information extraction. Experiments in detection and semantic enrichment show promising results of 94% correct semantization. Then, we integrate the metadata in an archaeological smart point cloud data structure allowing spatio-semantic queries related to CIDOC-CRM. Finally, a WebGL prototype is presented that leads to efficient communication between actors by proposing optimal 3D data visualizations as a basis on which interaction can grow.
Researchers ; Professionals ; Students ; General public ; Others
http://hdl.handle.net/2268/214931
10.3390/geosciences7040096
http://www.mdpi.com/2076-3263/7/4/96
https://www.researchgate.net/publication/320178371_3D_Point_Clouds_in_Archaeology_Advances_in_Acquisition_Processing_and_Knowledge_Integration_Applied_to_Quasi-Planar_Objects
https://www.mendeley.com/research-papers/3d-point-clouds-archaeology-advances-acquisition-processing-knowledge-integration-applied-quasiplana/
https://www.academia.edu/34769560/3D_Point_Clouds_in_Archaeology_Advances_in_Acquisition_Processing_and_Knowledge_Integration_Applied_to_Quasi-Planar_Objects
http://pointcloudproject.com/focus-on-my-research/
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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