In recent years, 3D building models have become increasingly widespread and are intensively exploited in fields of computer graphics and geometry processing. One of the common surface representations of 3D building models is polygon mesh, which is both compact and efficient in te
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In recent years, 3D building models have become increasingly widespread and are intensively exploited in fields of computer graphics and geometry processing. One of the common surface representations of 3D building models is polygon mesh, which is both compact and efficient in terms of exchange format
and data processing respectively. Downstream applications of polygon meshes can be found in the fields of urban planning, digital mapping, and fluid simulation.
However, the aforementioned applications usually require the input to be watertight and manifold, which is not always fulfilled by existing building models. Moreover, the interior structures of a building model are also considered redundant in certain applications. From such practical demands comes
our graduation project, i.e. trying to recover watertight and manifold outer surface from error-ridden 3D building models.
Existing methods with respect to outer surface extraction can be categorized into two types: surfaceoriented methods and volumetric methods. The former focuses on one particular type of artifacts and operates directly on the surfaces of the defective model. Since surface-oriented methods mainly introduce local operations where needed, unnecessary changes of the original model can be avoided and the result is of high fidelity. Whilst, the latter generates an intermediate representation of the original model, based on which the outer surface is extracted. The volumetric methods are more heuristic for our project since they are designed especially for multiple artifacts and the results are gauranteed with some desired properties.
In this thesis, we propose a hybrid approach for the extraction of outer surface from error-ridden 3D building models, which aims at recovering a watertight and manifold outer shell of the original model. The advantage of our method is that it is non-parametric, fully automatic, and have no assumptions for the input. Moreover, the small features of original model are kept to the greatest extent after processing.
Our method can be divided into four steps: 1) pre-processing, 2) constrained tetrahedralization, 3) classification, and 4) outer surface extraction. All six types of artifacts listed in this paper are gradually resolved during these steps, resulting in a watertight and manifold representation.
The results from our experiments turn out that our methodology can generate valid results in most cases, while preserving input faces and small features at the same time. Comparing with several stateof-the-art methods, our results still possess superior properties in terms of validity and integrity.
