City3D: Large-Scale Building Reconstruction from Airborne LiDAR Point Clouds

Abstract

We present a fully automatic approach for reconstructing compact 3D building models from large-scale airborne point clouds. A major challenge of urban reconstruction from airborne LiDAR point clouds lies in that the vertical walls are typically missing. Based on the observation that urban buildings typically consist of planar roofs connected with vertical walls to the ground, we propose an approach to infer the vertical walls directly from the data. With the planar segments of both roofs and walls, we hypothesize the faces of the building surface, and the final model is obtained by using an extended hypothesis-and-selection-based polygonal surface reconstruction framework. Specifically, we introduce a new energy term to encourage roof preferences and two additional hard constraints into the optimization step to ensure correct topology and enhance detail recovery. Experiments on various large-scale airborne LiDAR point clouds have demonstrated that the method is superior to the state-of-the-art methods in terms of reconstruction accuracy and robustness. In addition, we have generated a new dataset with our method consisting of the point clouds and 3D models of 20k real-world buildings. We believe this dataset can stimulate research in urban reconstruction from airborne LiDAR point clouds and the use of 3D city models in urban applications.

3D LoD2 and LoD3 Modeling of Buildings with Ornamental Towers and Turrets Based on LiDAR Data

“…Complex building tures, including ornamental features, were not visualized because only straight-lin elements were used in the modeling process. This problem had been previously r nized by Huang et al [35].…”

“…In the generated point clouds, subsets that represent roof planes are extracted by the developed algorithms [30,32]. In the next step, roof plane boundaries are modeled as straight-line segments, and the topological relationships between these elements are established [26,27,[32][33][34][35]. Building facades are usually difficult to model, due to incomplete datasets in point clouds.…”

“…This approach supported the development of numerous algorithms for automatically identifying and modeling buildings based on LiDAR data at the LOD2 level. The generated algorithms are based on modeled roof planes [32,35,36]. In the constructed models, the ground floor of a building is represented by the contour of the roof [34,35].…”

“…The generated algorithms are based on modeled roof planes [32,35,36]. In the constructed models, the ground floor of a building is represented by the contour of the roof [34,35]. This simplified approach was adopted to establish topological relationships between geometric objects in building models [18,35,37].…”

“…In the constructed models, the ground floor of a building is represented by the contour of the roof [34,35]. This simplified approach was adopted to establish topological relationships between geometric objects in building models [18,35,37]. The proposed methods and algorithms for modeling buildings at different levels of detail always give simplified results.…”