Feature-preserving mesh reconstruction from point clouds is challenging.Implicit methods tend to fit smooth surfaces and cannot be used to reconstruct sharp features.Explicit reconstruction methods are sensitive to no...Feature-preserving mesh reconstruction from point clouds is challenging.Implicit methods tend to fit smooth surfaces and cannot be used to reconstruct sharp features.Explicit reconstruction methods are sensitive to noise and only interpolate sharp features when points are distributed on feature lines.We propose a watertight surface reconstruction method based on optimal transport that can accurately reconstruct sharp features often present in CAD models.We formalize the surface reconstruction problem by minimizing the optimal transport cost between the point cloud and the reconstructed surface.The algorithm consists of initialization and refinement steps.In the initialization step,the convex hull of the point cloud is deformed under the guidance of a transport plan to obtain an initial approximate surface.Next,the mesh surface was optimized using operations including vertex relocation and edge collapses/fips to obtain feature-preserving results.Experiments demonstrate that our method can preserve sharp features while being robust to noise and missing data.展开更多
基金supported by the National Key R&D Program of China(2022YFB3303400)the National Natural Science Foundation of China(62272402,62372389)+1 种基金the Natural Science Foundation of Fujian Province(2022J01001)the Fundamental Research Funds for the Central Universities(20720220037)。
文摘Feature-preserving mesh reconstruction from point clouds is challenging.Implicit methods tend to fit smooth surfaces and cannot be used to reconstruct sharp features.Explicit reconstruction methods are sensitive to noise and only interpolate sharp features when points are distributed on feature lines.We propose a watertight surface reconstruction method based on optimal transport that can accurately reconstruct sharp features often present in CAD models.We formalize the surface reconstruction problem by minimizing the optimal transport cost between the point cloud and the reconstructed surface.The algorithm consists of initialization and refinement steps.In the initialization step,the convex hull of the point cloud is deformed under the guidance of a transport plan to obtain an initial approximate surface.Next,the mesh surface was optimized using operations including vertex relocation and edge collapses/fips to obtain feature-preserving results.Experiments demonstrate that our method can preserve sharp features while being robust to noise and missing data.
