面向城市更新的点云-BIM几何语义一体化既有建筑三维重建方法OA

This paper proposes a novel building information modeling(BIM)reconstruction methodology with geometric-semantic integration for exterior components of existing buildings,addressing the critical challenges of labor-intensive workflows and inconsistent quality in point cloud-based BIM reconstruction with urban renewal contexts.The Mask3D algorithm is utilized to achieve semantic instance segmentation and fine-grained classification of exterior point clouds.A series of component-oriented parametric decoupling algorithms enable precise parameter extraction through 2D-3D vision fusion integrated with topological constraint optimization.An adaptive heterogeneous data schema mapping interface performs structured processing of primitive parameters.A three-phase modeling methodology is designed to accomplish automated,rapid reconstruction of exterior BIM models.Case validation results indicate that this method achieves efficient reconstruction of BIM models integrating both precise geometric information(e.g.,position and dimensions)and rich semantic information(e.g.,material attributes and topological relationships).Quantitative analyses demonstrate reconstruction success rates of 96.7%and 93.6%across six exterior component categories,with wall reconstruction precision reaching centimeter-level accuracy and inter-component topological relationship retention rates exceeding 95%.