A Fast Mesh-Growing Algorithm for Manifold Surface Reconstruction

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 meshgrowing 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.

Surface reconstruction by computing restricted Voronoi cells in parallel

“…For example, The Ball Pivoting algorithms (BPA) [32,33] are local, optimized variants of the Alpha Shapes [34]. These algorithms can be parallelized to handle large datasets [35].…”

Low-Cost Methodology for Skin Strain Measurement of a Flexed Biological Limb

“…This triangulated surface is called the marker surface model. A publicly available MATLAB script [18], [19] is used to compute a Delaunay triangulation (a triangulation such that for each triangle, the circumcircle only encapsulates the triangle's vertices) of the marker centroid point cloud.…”

“…As a result, the number of triangles is constant and identifiable between two postures of the same object [20] and vertices can be uniquely corresponded between data sets. Triangles are corresponded using a mesh-growing algorithm [19]. A seed triangle is first manually identified on both postures (as highlighted by red, green, and blue points in Fig.…”

Reverse Engineering

“…The current implementation of the proposed method is roughly as fast as other recent popular methods. A new high-performance method for triangular mesh generation based on a mesh-growing approach is proposed in [12]. The performance of the proposed method has been compared with the performance of reference method with applications of the mesh-growing approaches to some benchmark point clouds and artificially noised test cases.…”