GCH 2022 - Eurographics Workshop on Graphics and Cultural Heritage

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https://diglib.eg.org/handle/10.2312/2633215

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Browsing GCH 2022 - Eurographics Workshop on Graphics and Cultural Heritage by Subject "Archaeology"

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    Automated Classification of Crests on Pottery Sherds Using Pattern Recognition on 2D Images
    (The Eurographics Association, 2022) Ritz, Martin; Santos, Pedro; Fellner, Dieter W.; Ponchio, Federico; Pintus, Ruggero
    Manual classification of artefacts is a labor intensive process. Based on 2D images and 3D scans of - for example - ceramic shards, we developed a pattern recognition algorithm which automatically extracts relief features for each newly recorded object and tries to automate the classification process. Based on characteristics found, previously unknown objects are automatically corelated to already classified objects of a collection exhibiting the greatest similarity. As a result, classes of artefacts form iteratively, which ultimately also corresponds to the overall goal which is the automated classification of entire collections. The greatest challenge in developing our software approach was the heterogeneity of reliefs, and in particular the fact that current machine learning approaches were out of question due to the very limited number of objects per class. This led to the implementation of an analytical approach that is capable of performing a classification based on very few artefacts.
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    A Concept for Reconstructing Stucco Statues from historic Sketches using synthetic Data only
    (The Eurographics Association, 2022) Pöllabauer, Thomas; Kühn, Julius; Ponchio, Federico; Pintus, Ruggero
    In medieval times, stuccoworkers used a red color, called sinopia, to first create a sketch of the to-be-made statue on the wall. Today, many of these statues are destroyed, but using the original drawings, deriving from the red color also called sinopia, we can reconstruct how the final statue might have looked. We propose a fully-automated approach to reconstruct a point cloud and show preliminary results by generating a color-image, a depth-map, as well as surface normals requiring only a single sketch, and without requiring a collection of other, similar samples. Our proposed solution allows real-time reconstruction on-site, for instance, within an exhibition, or to generate a useful starting point for an expert, trying to manually reconstruct the statue, all while using only synthetic data for training.
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    Lithic Feature Identification in 3D based on Discrete Morse Theory
    (The Eurographics Association, 2022) Bullenkamp, Jan Philipp; Linsel, Florian; Mara, Hubert; Ponchio, Federico; Pintus, Ruggero
    Neanderthals and our human ancestors have coexisted for a large period of time sharing many things in common including the production of tools, which are among the few remaining artefacts providing a possible insight into the different paths of evolvement and extinction. These earliest tools were made of stone using different strategies to reduce a rather round stone to a sharp tool for slicing, scraping, piercing or chopping. The type of strategy is assumed to be correlated either with our ancestors or the Neanderthals. Recent research uses computational methods to analyse shapes of lithic artefacts using Geometric MorphoMetrics (GMM) as known in anthropology. As the main criteria for determining a production strategy are morphologic measures like shape, size, roughness of convex ridges and concave scars, we propose a new method based on discrete Morse theory for surface segmentation to enable GMM analysis in future work. We show the theoretical concepts for the proposed segmentation, which have been applied to a dataset being available via Open Access. For validation we have created a statistically significant subset of segmented simple and complex lithic tools, which have been manually segmented by an expert as ground truth. We finally show results of our experiments on this real dataset.