GCH 2023 - Eurographics Workshop on Graphics and Cultural Heritage

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https://diglib.eg.org/handle/10.2312/3543875

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Browsing GCH 2023 - Eurographics Workshop on Graphics and Cultural Heritage by Subject "Applied computing → Fine arts"

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    High Resolution 2D-/3D-Scanning and Deep Learning Segmentation for Digitization of Fragmented Wall Paintings
    (The Eurographics Association, 2023) Kroeger, Ole; Krumpek, Oliver; Koch, Paul; Pape, Martin; Schneider, Jan; Krüger, Jörg; Bucciero, Alberto; Fanini, Bruno; Graf, Holger; Pescarin, Sofia; Rizvic, Selma
    The preservation and study of mural wall paintings often involve the collection of numerous fragments with unknown context. In this paper the authors present a case study involving a Roman wall painting discovered in 2013 at the European Cultural Park Bliesbruck-Reinheim. The objective of this work was to develop a semi-automated assistance system for the digitization, visualization, and digital repositioning of the Roman wall painting fragments. Therefore an easy-to-use scanner system was developed, that captures high-resolution 2D images of the front and back surfaces of the fragments, along with a height map of the backside. The contributing partners also developed a control and operating software for the scanner, as well as an automated software platform for visualization and repositioning of the digital fragments. The contributions of this paper include the introduction of a ML-based algorithm for background subtraction and segmentation of the front surface of the fragments. The technical realisation for fast and accurate image acquisition of the fragments, including sensor registration and highresolution capture, has been worked out. The system calibration process, hardware setup and data correction techniques are described in detail. Additionally, the challenges of pixel-wise image segmentation for distinguishing between background, inner contour (wall painting), and outer contour (fragment surface without painting) are discussed. Our proposed approach overcomes the limitations of training ML algorithms on high-resolution images by employing patch-wise training and leveraging small features instead of large-scale features. The digitization and segmentation process demonstrated promising results in preserving and reconstructing the roman wall painting fragments. The findings of this study contribute to the field of cultural heritage preservation and provide valuable insights as the developed equipment and methods are highly transferable to future digitization projects.
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    The Scream (ca. 1910) through the Years: from Photographic Documentation to Spatio-Temporal Modelling
    (The Eurographics Association, 2023) Ciortan, Irina; Trumpy, Giorgio; Sandu, Irina; Bjørngård, Halvor; Bucciero, Alberto; Fanini, Bruno; Graf, Holger; Pescarin, Sofia; Rizvic, Selma
    The Scream (ca. 1910) is one of Edvard Munch's representations of the well-known scene of a man awestruck by the beauty and colors of the sunset over the fjord, painted in oil and tempera on cardboard. Given the age of the artwork, it is expected that its appearance has significantly changed since its creation to the current state. Previous studies found that the yellow and dark red hues that depict the sky are especially sensitive to moisture and light exposure, respectively. In addition, several film photographs were taken of the painting between 1970 and 2003. In this work, we aim to use these photographs in an attempt to model the changes that the artwork withstood, and reconstruct its past appearance. We perform color correction of the photographs, by comparing the unfaded values in the films against reference values in the current version of the painting. To define the reference values, we use the existing knowledge on the highly sensitive areas and other damages that occured to the painting. Finally, we obtain a color transformation function that facilitates the digital rejuvenation of the painting appearance.