A semantics-constrained profiling approach to complex 3D city models

Abstract

A complex 3D city model contains detailed descriptions of both its appearance and its internal structure, including architectural components. Because of the topological complexity and the large volumes of data in such models, profiling is an effective method to present the internal structure, the distributed characteristics, and the hierarchical relationships of the model to provide intuitive visual information to the viewer and to reveal the relationships between the elements of the model and the whole. However, with commonly used boundary descriptions, it is difficult to comprehensively preserve the consistency of three-dimensional profiling using existing algorithms based on geometric constraints. This paper proposes a novel semantics-constrained profiling approach to ensure the consistency of the geometrical, topological, and semantic relationships when profiling complex 3D city models. The approach transforms the 3D model’s boundary description, defined using the CityGML standard of the Open Geospatial Consortium (OGC), into a set of unified volumetric features described as solids. This approach is characterized by (1) the use of the concepts of semantic relationships, virtual edges, and virtual surfaces; (2) the semantic analysis of 3D models and the extraction of volumetric features as basic geometric analytic units; (3) the completion of structural connectivity and space coverage for each volumetric feature, which is represented as a solid model; and (4) the use of a reliable 3D Boolean operation for efficient and accurate profiling. A typical detailed 3D museum model is used as an example to illustrate the profiling principle, and the experimental results demonstrate the correctness and effectiveness of this approach.