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dc.contributor.authorCiortan, Irina Mihaelaen_US
dc.contributor.authorPintus, Ruggeroen_US
dc.contributor.authorMarchioro, Giacomoen_US
dc.contributor.authorDaffara, Claudiaen_US
dc.contributor.authorGiachetti, Andreaen_US
dc.contributor.authorGobbetti, Enricoen_US
dc.contributor.editorChiara Eva Catalano and Livio De Lucaen_US
dc.date.accessioned2016-10-05T06:27:43Z
dc.date.available2016-10-05T06:27:43Z
dc.date.issued2016
dc.identifier.isbn978-3-03868-011-6
dc.identifier.issn2312-6124
dc.identifier.urihttp://dx.doi.org/10.2312/gch.20161396
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/gch20161396
dc.description.abstractWe present a practical acquisition and processing pipeline to characterize the surface structure of cultural heritage objects. Using a free-form Reflectance Transformation Imaging (RTI) approach, we acquire multiple digital photographs of the studied object shot from a stationary camera. In each photograph, a light is freely positioned around the object in order to cover a wide variety of illumination directions. Multiple reflective spheres and white Lambertian surfaces are added to the scene to automatically recover light positions and to compensate for non-uniform illumination. An estimation of geometry and reflectance parameters (e.g., albedo, normals, polynomial texture maps coefficients) is then performed to locally characterize surface properties. The resulting object description is stable and representative enough of surface features to reliably provide a characterization of measured surfaces. We validate our approach by comparing RTI-acquired data with data acquired with a high-resolution microprofilometer.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.4.1 [Image processing and Computer Vision]
dc.subjectDigitization and Image Capture
dc.subjectImaging Geometry
dc.titleA Practical Reflectance Transformation Imaging Pipeline for Surface Characterization in Cultural Heritageen_US
dc.description.seriesinformationEurographics Workshop on Graphics and Cultural Heritage
dc.description.sectionheadersAcquisition and Visualisation
dc.identifier.doi10.2312/gch.20161396
dc.identifier.pages127-136


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