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dc.contributor.authorHouska, Peteren_US
dc.contributor.authorLengauer, Stefanen_US
dc.contributor.authorKarl, Stephanen_US
dc.contributor.authorPreiner, Reinholden_US
dc.contributor.editorHulusic, Vedad and Chalmers, Alanen_US
dc.date.accessioned2021-11-02T08:55:54Z
dc.date.available2021-11-02T08:55:54Z
dc.date.issued2021
dc.identifier.isbn978-3-03868-141-0
dc.identifier.issn2312-6124
dc.identifier.urihttps://doi.org/10.2312/gch.20211417
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/gch20211417
dc.description.abstractAn important task in archaeological research is the comparison of painted motifs on ancient vessels and the analysis of their painting style. Ideally, the pottery objects are available as scanned 3D models, from which the painted surface can be unrolled and potential distortions minimized, so that the vase painting and its individual motifs can be directly inspected. Unfortunately, the percentage of digitally captured vessels is small compared to the large body of cataloged photographs. In this paper, we present a method that creates distortion-minimized unrollings of painted pottery surfaces directly from a small set of photographs. We achieve this by exploiting prior knowledge about the data, namely that most objects exhibit rotational symmetry and that strict guidelines were followed when capturing photographs of the ancient vases. Based on the distinctly visible object silhouettes in the photographs we are able to extract proxy geometries of the objects which we encode as per-view geometric maps. By stitching the single-view data, we obtain a combined map capturing the geometry and texture of the entire painted surface. This enables us to minimize typical projective distortions by elastic relaxation. Our pipeline works entirely in 2D image space, circumventing time-consuming 3D scans and surface reconstructions of (often inaccessible) vessels. Using a combination of CPU-based image processing and GPU-based relaxation, results are produced in only a few minutes.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectImage processing
dc.titleDirect Elastic Unrollings of Painted Pottery Surfaces from Sparse Image Setsen_US
dc.description.seriesinformationEurographics Workshop on Graphics and Cultural Heritage
dc.description.sectionheadersArt and Cultural Heritage
dc.identifier.doi10.2312/gch.20211417
dc.identifier.pages131-140


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