A feature preserved mesh simplification algorithm

Large-volume mesh model faces challenge in rendering, storing, and transmission due to large size of polygon data. Mesh simplification is one of solutions to reduce the data size. This paper presents a mesh simplification method based on feature extraction with curvature estimation to triangle mesh. The simplified topology preserves good geometrical features in the area with distinct features, that is, coarse simplified mesh in the flat region and fine simplified mesh around the areas of crease and corner. Sequence of mesh simplification is controlled on the basis of geometrical feature sensitivity, which results in reasonable simplification topology with less data size. This algorithm can decrease the size of the file by largely simplifying flat areas and preserving the geometric feature as well

Moment-based metrics for mesh simplification

International audienceMesh simplification is an important research topic in scientific visualization and virtual reality. The simplification metric is a key issue of a simplification algorithm. In this study, two new simplification metrics based on surface moments and volume moments are proposed, which take the difference between the moments defined by the original mesh and those of the simplified mesh as the objective function. These metrics were used in an edge collapse scheme in order to prove their usability in the mesh simplification procedure. For a given maximum order and the number of triangles required, the optimal mesh with a minimum moment difference from the original mesh can be determined. The procedures are applied to some models and better results are obtained in comparison with some known algorithms