A data-driven approach for adding facade details to textured LoD2 CityGML models

• Main Authors: Zhang, Xingzi, Lippoldt, Franziska, Chen, Kan, Johan, Henry, Erdt, Marius
• Other Authors: School of Computer Science and Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2019
• Subjects: Data-driven; Facade Details Addition; Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/90067; http://hdl.handle.net/10220/49839
• Institution: Nanyang Technological University

LoD3 CityGML models (with facade elements, e.g., windows and doors) have many applications, however, they are not easy to acquire, while LoD2 models (only roofs and walls) are currently largely available. In this paper, we propose to generate LoD3 models by adding facade details to textured LoD2 models using a data-driven approach. The existing reconstruction-based methods usually require high costs to obtain plausible LoD3 models. Instead, our proposed data-driven method is based on automatically detecting the facade elements from the texture images and interactively selecting matched models from a 3D facade element model database, then deforming and stitching them with the input LoD2 model to generate a LoD3 model. In this manner, our method is free from reconstruction errors, such as non-symmetrical artifacts and noise, and it is practically useful for its simplicity and effectiveness.