The VOLTA project is a RISE Marie-Curie action designed to realize Research & Innovation (R&I) among intersectoral partners to exchange knowledge, methods and workflows in the geospatial field. To accomplish its objectives, the main R&I activities of VOLTA are divided in four interlinked Work Packages with two transversal ones responsible for knowledge transfer & training as well as dissemination of the project results. The research activities and knowledge transfer are performed with a series of secondments between partners. The consortium is composed of 13 partners from academic & research institutions, industrial partners and national mapping agencies. The Romanian National Center of Cartography is part of this research project and in this article the achievements of the secondment at Bruno Kessler Foundation in Trento (Italy) are given. The main goal of the exchange was to generate level of detail - LOD2 building models in an automated manner from photogrammetric point clouds and without any ancillary data. To benchmark existing commercial solutions for the realization of LOD2 building models, we tested Building Reconstruction. This program generates LOD2 models starting from building footprints, digital terrain model (DTM) and digital surface model (DSM). The presented work examined a research and a commercial-based approach to reconstruct LOD2 building models from point clouds. The full paper will report all technical details of the work with insight analyses and comparisons.
Biljecki, F., Ledoux, H., Stoter, J., 2016. An improved LOD specification for 3D building models: Computers, Environment and Urban Systems.
Dorninger, P. & Pfeifer, N., 2008. A Comprehensive Automated 3D Approach for Building Extraction, Reconstruction, and Regularization from Airborne Laser Scanning Point Clouds. Sensors. Vol. 8:11. pp. 7323-7343. DOI: 10.3390/s8117323. ISSN 1424-8220.
Gröger, G. & Plümer, L., 2012. CityGML – Interoperable semantic 3D city models. ISPRS Journal of Photogrammetry and Remote Sensing. Vol. 71. pp 12-33. DOI: 10.1016/j.isprsjprs.2012.04.004. ISSN: 0924-2716.
Haala, N., Kada, M., 2010. An Update on Automatic 3D Building Reconstruction. Isprs Journal of Photogrammetry and Remote Sensing 65, 570-580.
Lafarge, F. & Mallet, C., 2012. Creating Large-Scale City Models from 3D-Point Clouds: A Robust Approach with Hybrid Representation. International journal of computer vision 99, 69-85.
Nan, L., Wonka, P., 2017. PolyFit: Polygonal Surface Reconstruction from Point Clouds: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Venice, Italy, pp. 2353-2361.
Nex, F., Gerke, M., Remondino, F., Przybilla, H.-J., Bäumker, M., Zurhorst, A., 2015. ISPRS benchmark for multi-platform photogrammetry: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. II-3/W4, pp. 135-142.
Ozdemir, E., Remondino, F., 2018. Segmentation of 3D photogrammetric point cloud for 3D building modeling: ISPRS International archives of photogrammetry, remote sensing and spatial information sciences, Vol. XLII-4/W10, pp. 135-142.
Rabbani, T., van den Heuvel, F. A., Vosselman, G., 2006. Segmentation of point clouds using smoothness constraint: International archives of photogrammetry, remote sensing and spatial information sciences, Vol. 36(5).
Remondino, F., Gerke, M., 2015. Oblique Aerial Imagery – A Review: Proc. Photogrammetric Week 2015, D. Fritsch (Ed.), pp. 75-83.
Remondino, F., Toschi, I., Gerke, M., Nex, F., Holland, D., McGill, A., Talaya Lopez, J., Magarinos, A., 2016. Oblique Aerial Imagery for NMA – Some Best Practices: International archives of photogrammetry, remote sensing and spatial information sciences, Vol. XLI-B4.