Progressive Dilution of Point Clouds Considering the Local Relief for Creation and Storage of Digital Twins of Cultural Heritage

Abstract

Currently, the creation of digital copies (digital twins) of various objects by remote sensing methods producing point clouds is becoming commonplace. This might be particularly important for the digital preservation of historical objects. Such clouds are typically primarily acquired as unordered sets of points with regular dense spacing, making the clouds huge in size, which causes such clouds to be difficult to process, store and share. The clouds are, therefore, usually diluted before use, typically through uniform dilution with a set spacing; such dilution can, however, lead to the loss of detail in the resulting cloud (washed-out edges and fine features). In this paper, we present an easy-to-use and computationally inexpensive progressive dilution method preserving detail in highly rugged/curved areas while significantly reducing the number of points in flat areas. This is done on the basis of a newly proposed characteristic T, which is based on the local scattering of the cloud (i.e., on the ruggedness of the local relief). The performance of this algorithm is demonstrated on datasets depicting parts of historic buildings of different characters. The results are evaluated on the basis of (a) root mean square deviation (RMSD) between the original and diluted clouds, (b) of visual evaluation of the differences and (c) of reduction in the point cloud size, demonstrating an excellent performance of the algorithm with a minimum loss of detail while significantly reducing the point clouds (approx. by 47–66% compared to the corresponding uniform dilution for individual datasets)

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Determination of Accuracy and Usability of a SLAM Scanner GeoSLAM Zeb Horizon: A Bridge Structure Case Study

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