Background Three-dimensional(3D)building models with unambiguous roof plane geometry parameters,roof structure units,and linked topology provide essential data for many applications related to human activities in urba...Background Three-dimensional(3D)building models with unambiguous roof plane geometry parameters,roof structure units,and linked topology provide essential data for many applications related to human activities in urban environments.The task of 3D reconstruction from point clouds is still in the development phase,especially the recognition and interpretation of roof topological structures.Methods This study proposes a novel visual perception-based approach to automatically decompose and reconstruct building point clouds into meaningful and simple parametric structures,while the associated mutual relationships between the roof plane geometry and roof structure units are expressed by a hierarchical topology tree.First,a roof plane extraction is performed by a multi-label graph cut energy optimization framework and a roof structure graph(RSG)model is then constructed to describe the roof topological geometry with common adjacency,symmetry,and convexity rules.Moreover,a progressive roof decomposition and refinement are performed,generating a hierarchical representation of the 3D roof structure models.Finally,a visual plane fitted residual or area constraint process is adopted to generate the RSG model with different levels of details.Results Two airborne laser scanning datasets with different point densities and roof styles were tested,and the performance evaluation metrics were obtained by International Society for Photogrammetry and Remote Sensing,achieving a correctness and accuracy of 97.7%and 0.29m,respectively.Conclusions The standardized assessment results demonstrate the effectiveness and robustness of the proposed approach,showing its ability to generate a variety of structural models,even with missing data.展开更多
基金Supported by the National Natural Science Foundation of China(41901405,41725005,41531177)and the National Key Research and Development Program of China(2016YFF0103501).
文摘Background Three-dimensional(3D)building models with unambiguous roof plane geometry parameters,roof structure units,and linked topology provide essential data for many applications related to human activities in urban environments.The task of 3D reconstruction from point clouds is still in the development phase,especially the recognition and interpretation of roof topological structures.Methods This study proposes a novel visual perception-based approach to automatically decompose and reconstruct building point clouds into meaningful and simple parametric structures,while the associated mutual relationships between the roof plane geometry and roof structure units are expressed by a hierarchical topology tree.First,a roof plane extraction is performed by a multi-label graph cut energy optimization framework and a roof structure graph(RSG)model is then constructed to describe the roof topological geometry with common adjacency,symmetry,and convexity rules.Moreover,a progressive roof decomposition and refinement are performed,generating a hierarchical representation of the 3D roof structure models.Finally,a visual plane fitted residual or area constraint process is adopted to generate the RSG model with different levels of details.Results Two airborne laser scanning datasets with different point densities and roof styles were tested,and the performance evaluation metrics were obtained by International Society for Photogrammetry and Remote Sensing,achieving a correctness and accuracy of 97.7%and 0.29m,respectively.Conclusions The standardized assessment results demonstrate the effectiveness and robustness of the proposed approach,showing its ability to generate a variety of structural models,even with missing data.
