Automated constructing multi-resolution 3D building models is an important issue in the contexts of virtual reality, progressive transmission and 3D GIS. This paper proposes a novel method to generate multi-resolution representations of the 3D complex building model with features preservation based on cell clustering. The quadratic error function is constructed to efficiently measure the clustering error of each cell. First, the 3D complex building model is converted into volumetric representation. Then, the boundary cells are progressively clustered into a coarser version and a corresponding cell binary tree is generated. Finally, the simplified building model can be extracted according to a modified dual contouring algorithm. The experimental results show that the proposed approach provides an efficient and robust solution for the automated generation of multi-resolution building models, with capability of preserving the dominated structure features.
Due to their limited expressive capabilities and computational resources, typical mobile devices are still not appropriate for real-time 3D navigation, in particular when widespread building models in the urban environments have a very detailed geometry. In order to better balance the capability of mobile devices and the perception demands of the users in 3D navigation, this paper proposes an automated algorithm to generate structure-preserving abstractions of building models for the purpose of suitable dataset preparation. Building models are segmented into different structural parts, and each structural part is approximated by a convex polyhedron, then the convex parts are combined together to achieve the ultimate abstraction. The robustness and efficiency of the algorithm is proved by extensive experiments.
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