| dc.description.abstract | Nowadays, three dimensional (3D) building model has been widely used in urban planning, landscape simulation, 3D navigation, disaster prevention simulation and preservation of architectural heritage sites. Especially for cultural heritage, applying 3D building information effectively and representing the characteristics of structures fast and accurately are important tasks to enhance cultural research and promote the maintenance of management. There are several representations commonly used for building models such as wire frame, parametric, mesh models, and so on. An effective approach is to use parameterized models describing the most common building types. In addition, another common approach to represent buildings is using meshes. Meshes or triangulated local adaptive meshes can be used to describe complex objects in detail. Accordingly, this research proposes a two-step, coarse-to-fine strategy to create three-dimensional models of complicated architectural structures or archeological sites based on point clouds data. The proposed approach creates a sparse model first and then the fine geometric details will be added gradually.
In this study, digital single-lens reflex (DSLR) camera is used to collect the original image data of targets. Then, 3D point clouds are generated from these images using Structure from Motion (SFM) algorithms. Parameters for constructing parametric models are identified from the point clouds. Moreover, Poisson surface reconstruction is carried out to generate mesh models. The integration of parametric and mesh models is the major subsequent task in this research, which includes three steps. Firstly, detect boundary points for connecting parameter models and mesh models. Next, generate a new junction on the pre-integrated surfaces of the parameter models. Finally, a new mesh model is generated in the pre-integrated space. The result demonstrates a hybrid model of complicated buildings with different Levels of Details (LOD).
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