Abstract
3D surface scanners can only record discrete data sets (point clouds). The meshing process is a complex issue and in the last years there were lots of algorithms developed to solve this problem. In this work an algorithm will be presented, which generates a textured regular surface model from arbitrary scattered 3D scan data. A color-coded normal field, delivered with the input data, allows for a meaningful projection of curved surfaces and, therefore, for iteratively building up a highly detailed regular mesh. As most scanners are able to pointwise record true color information, such a mesh can serve as a template to automatically generate a texture. After further reducing mesh complexity by using LOD-techniques, we can map the appropriate texture via classical UV-mapping onto the reduced mesh, such that the detailed color information of the surface is being preserved, even for low polygon surface models.
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Acknowledgements
We would like to thank the Interdisciplinary Center for Scientific Computing (IWR) of the Heidelberg University for technical and computational support. Our thanks also go to Karsten Leuthold, Survey Service, CALLIDUS-Competence Center, for generously let us use the data from the scans of the excavations at Lorsch Abbey and several locations in Heidelberg.
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Hoppe, C., Krömker, S. (2013). Towards an Automated True Color Projection onto Adaptively Reduced Point Data from 3D Surface Scans. In: Bock, H., Jäger, W., Winckler, M. (eds) Scientific Computing and Cultural Heritage. Contributions in Mathematical and Computational Sciences, vol 3. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28021-4_3
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DOI: https://doi.org/10.1007/978-3-642-28021-4_3
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