Today's spatially aware users are becoming more interested in retrieving personalised and task relevant information, requiring detailed 3D city models linked to non-spatial attribute data. However, current implementations of 3D city models are typically LoD2 that don't include geometric or attribute details about many visible features (e.g. rooms) of a building. As such, value-added applications developed for web-based and wireless platforms are limited to querying for available non-spatial business data at the building level only. To overcome this, geometrically accurate 3D building models are necessary to enable users to visualize, interact, and query for task specific non-spatial business data. This paper proposes a workflow for creating detailed 3D building models with LoD3 from TLS data and uploading these models into Google Earth so that users can then explore the non-spatial business data of a building and its sub-components (e.g. windows, doors, rooms). Processing bottlenecks of the proposed workflow for detailed 3D building reconstruction are also discussed. © 2013 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Truong-Hong, L., Pham Thi, T. T., Yin, J., & Carswell, J. D. (2013). Preparing detailed 3D building models for Google earth integration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7974 LNCS, pp. 61–76). Springer Verlag. https://doi.org/10.1007/978-3-642-39649-6_5
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