Towards Semi-Automatic Scaling Detection on Flat Stones

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dc.contributor.authorMuñoz-Pandiella, Imanolen_US
dc.contributor.authorAkoglu, Kirazen_US
dc.contributor.authorBosch, Carlesen_US
dc.contributor.authorRushmeier, Hollyen_US
dc.contributor.editorTobias Schreck and Tim Weyrich and Robert Sablatnig and Benjamin Stularen_US
dc.date.accessioned2017-09-27T06:39:19Z
dc.date.available2017-09-27T06:39:19Z
dc.date.issued2017
dc.description.abstractIn Cultural Heritage projects, it is very important to identify and track weathering effects on monuments in order to design and test conservation strategies. Currently, this mapping is manual work performed by experts based on what they observe and their experience. In this paper, we present a workflow to map the weathering effect known as ''scaling'' on monuments with very little user interaction. First, we generate a 3D model of the monuments using photogrammetry techniques. Then, we reduce the noise in the acquired data using an adaptive and anisotropic filter. After that, we estimate the original shape of the surface before the weathering effects using the RANSAC algorithm. With this information, we perform a geometrical analysis to detect the features affected by this weathering effect and compute their characteristics. Then, we map the regions that have suffered scaling using the detected features and a segmentation based on the distance between the mesh and the unweathered surface. Our technique results can be very useful to understand the level of weathering of a monument and to trace the weathered parts through time automatically.en_US
dc.description.sectionheadersAcquisition and Analysis
dc.description.seriesinformationEurographics Workshop on Graphics and Cultural Heritage
dc.identifier.doi10.2312/gch.20171291
dc.identifier.isbn978-3-03868-037-6
dc.identifier.issn2312-6124
dc.identifier.pages49-58
dc.identifier.urihttps://doi.org/10.2312/gch.20171291
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/gch20171291
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectShape analysis
dc.subjectMesh geometry models
dc.subjectHuman
dc.subjectcentered computing
dc.subjectScientific visualization
dc.titleTowards Semi-Automatic Scaling Detection on Flat Stonesen_US
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GCH 2017 - Eurographics Workshop on Graphics and Cultural Heritage