Abstract
The preservation of cultural heritage assets of all kind is an important task for modern civilizations. This also includes tools and instruments that have been used in the previous decades and centuries. Along with the industrial revolution 200 years ago, mechanical and electrical technologies emerged, together with optical instruments. In the meantime, it is not only museums who showcase these developments, but also companies, universities, and private institutions. Gyroscopes are fascinating instruments with a history dating back 200 years. When J.G.F. Bohnenberger presented his machine to his students in 1810 at the University of Tuebingen, Germany, nobody could have foreseen that this fascinating development would be used for complex orientation and positioning. At the University of Stuttgart, Germany, a collection of 160 exhibits is available and in transition towards their sustainable future. Here, the systems are digitized in 2D, 2.5D, and 3D and are made available for a worldwide community using open access platforms. The technologies being used are computed tomography, computer vision, endoscopy, and photogrammetry. We present a novel workflow for combining voxel representations and colored point clouds, to create digital twins of the physical objects with 0.1 mm precision. This has not yet been investigated and is therefore pioneering work. Advantages and disadvantages are discussed and suggested work for the near future is outlined in this new and challenging field of tech heritage digitization.
Highlights
The preservation of cultural heritage assets is an important task of modern civilizations
The structure is as follows: after the introductory Section 1 we describe the novelty of this work in combining 3D models of geometric computer vision with 3D voxels of computed tomography
This paper has demonstrated that the 2D, 2.5D, and 3D digitization of tech heritage objects is a challenge that can be mastered through the combining of different technologies
Summary
The preservation of cultural heritage assets is an important task of modern civilizations. As will be shown later, sensor fusion for this combination is only possible with endoscopy and CV/photogrammetry, as both generate optical image blocks to be processed by SfM and DIM in one processing step This leads to consistent alignments and co-registered colored 3D point clouds. We define a seven parameter spatial similarity transformation embedded in an adjustment model, to co-register the 3D CT voxel clouds with the 3D point clouds of CV/photogrammetry, and to achieve quality measures for the registration in the form of unit weight variances and standard deviations. After an initial application of the ICP algorithm with a threshold of 0.05 mm using OS libraries, we chose u = 4 and u = 10 joint corners (control points) for the seven parameter transformations of the merged point clouds, obtaining improved registration results with the following quality measures for precision:. It is noted here that the data fusion of CT and CV/photogrammetry can provide digital twins with a precision of 0.1 mm
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