An Annotation Tool for Digital Restoration of Wall Paintings

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dc.contributor.authorBarreiro Díaz, Alberten_US
dc.contributor.authorMunoz-Pandiella, Imanolen_US
dc.contributor.authorBosch, Carlesen_US
dc.contributor.authorAndujar, Carlosen_US
dc.contributor.editorPonchio, Federicoen_US
dc.contributor.editorPintus, Ruggeroen_US
dc.date.accessioned2022-09-26T09:59:51Z
dc.date.available2022-09-26T09:59:51Z
dc.date.issued2022
dc.description.abstractAntique paintings are essential to study and understand our past. Paintings, and specifically mural paintings, are delicate artworks that are affected by multiple deterioration conditions. Weathering and human interventions cause different damage problems, and physical and chemical changes degrade their visual color appearance. As a consequence, art historians and archaeologists require a huge effort to attempt to rebuild their original appearance. The annotation of digital images of the paintings is a valuable tool in this process. In this paper we analyze major requirements from art historians concerning the annotation of painting regions from the point of view of digital restoration. We also describe a tool prototype (based on TagLab) intended to facilitate the annotation and segmentation of mural paintings. The tool assists art historians in formulating multiple hypotheses on the original appearance by supporting multiple annotation layers for degradation and color, providing both hand-drawn and semi-automatic segmentation, and offering web-based dissemination and sharing of the annotations through the W3C Web Annotation Data Model.en_US
dc.description.sectionheadersSession 2
dc.description.seriesinformationEurographics Workshop on Graphics and Cultural Heritage
dc.identifier.doi10.2312/gch.20221220
dc.identifier.isbn978-3-03868-178-6
dc.identifier.issn2312-6124
dc.identifier.pages33-36
dc.identifier.pages4 pages
dc.identifier.urihttps://doi.org/10.2312/gch.20221220
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/gch20221220
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Applied computing --> Fine arts; Computing methodologies --> Image processing
dc.subjectApplied computing
dc.subjectFine arts
dc.subjectComputing methodologies
dc.subjectImage processing
dc.titleAn Annotation Tool for Digital Restoration of Wall Paintingsen_US
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GCH 2022 - Eurographics Workshop on Graphics and Cultural Heritage