"In a previous paper these authors presented a new mesh-growing approach based on the Gabriel 2 – Simplex (G2S) criterion. If compared with the Cocone family and the Ball Pivoting methods, G2S demonstrated to be competitive in terms of tessellation rate, quality of the generated triangles and defectiveness produced when the surface to be reconstructed was locally flat. Nonetheless, its major limitation was that, in the presence of a mesh which was locally non – flat or which was not sufficiently sampled, the method was less robust and holes and non – manifold vertices were generated. In order to overcome these limitations, in this paper, the performance of the G2S mesh-growing method is fully improved in terms of robustness. The performances of the new version of the G2S approach (in the following Robust G2S) has been compared with that of the old one, and that of the Cocone family and the Ball Pivoting methods in the tessellation of some benchmark point clouds and artificially noised test cases. The results obtained show that the use of the Robust G2S is advantageous, as opposed to the other methods here considered, even in the case of noised point clouds. Unlike the other methods, the one which is proposed preserves manifoldness and geometric details of the point cloud to be meshed."

A Fast Mesh-Growing Algorithm For Manifold Surface Reconstruction

DI ANGELO, LUCA;DI STEFANO, PAOLO;
2013-01-01

Abstract

"In a previous paper these authors presented a new mesh-growing approach based on the Gabriel 2 – Simplex (G2S) criterion. If compared with the Cocone family and the Ball Pivoting methods, G2S demonstrated to be competitive in terms of tessellation rate, quality of the generated triangles and defectiveness produced when the surface to be reconstructed was locally flat. Nonetheless, its major limitation was that, in the presence of a mesh which was locally non – flat or which was not sufficiently sampled, the method was less robust and holes and non – manifold vertices were generated. In order to overcome these limitations, in this paper, the performance of the G2S mesh-growing method is fully improved in terms of robustness. The performances of the new version of the G2S approach (in the following Robust G2S) has been compared with that of the old one, and that of the Cocone family and the Ball Pivoting methods in the tessellation of some benchmark point clouds and artificially noised test cases. The results obtained show that the use of the Robust G2S is advantageous, as opposed to the other methods here considered, even in the case of noised point clouds. Unlike the other methods, the one which is proposed preserves manifoldness and geometric details of the point cloud to be meshed."
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/88963
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