Public Building Geometric Models From Point Clouds: A multidimensional quality evaluation framework

Dong Chen, Chenwei Zhu, Zhenxin Zhang, Jiaming Na, Yueqian Shen, Yanming Chen, Jiju Peethambaran, Liqiang Zhang

Abstract: With the rapid development of the low-altitude economy, the application of 3D building geometric models has become increasingly critical in fields such as urban planning and management, disaster emergency response, virtual reality, augmented reality, and digital twins. Due to the advancements in fundamental surveying and mapping technologies as well as computer vision, datasets of building geometric models based on ubiquitous point clouds have continuously emerged. However, the created models often suffer from low lightweight properties, strong dependence on prior knowledge of building structures, topological inconsistency, and insufficient or even absent semantic representation. These problems have resulted in building model datasets exhibiting significant disparities in geometric accuracy, topological structure, and semantic richness, alongside a lack of unified quality assessment standards. To address this, this article proposes a multidimensional quality evaluation framework for building geometric models, encompassing aspects such as geometric accuracy, topological correctness, semantic richness, lightweight properties, and model modality. This framework is employed to comprehensively evaluate six representative building model datasets. By examining common issues in existing datasets, such as geometric distortions, topological errors, and semantic deficiencies, a series of optimization strategies and solutions are proposed. Considering diverse application requirements, this article emphasizes balance among geometric accuracy, topological relationships, semantic richness, and lightweight to meet the demands of multiscenario applications. Furthermore, the article explores future directions for the construction of building model datasets, recommending a focus on multilevel detail representation, uncertainty assessment of quality, and alignment with practical application demands. These efforts aim to drive the optimization and intelligent development of 3D building models, providing higherquality support for applications such as digital twins and the low-altitude economy.

External IDs:doi:10.1109/mgrs.2025.3618468