A data reduction scheme for triangulated surfaces
Computer Aided Geometric Design
Surface simplification using quadric error metrics
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Proceedings of the conference on Visualization '01
Efficient simplification of point-sampled surfaces
Proceedings of the conference on Visualization '02
Constructing Hierarchies for Triangle Meshes
IEEE Transactions on Visualization and Computer Graphics
Convection-Driven Dynamic Surface Reconstruction
SMI '05 Proceedings of the International Conference on Shape Modeling and Applications 2005
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This study presents a novel rapid and effective point simplification algorithm based on point clouds without using either normal or connectivity information. Sampled points are clustered based on shape variations by octree data structure, an inner point distribution of a cluster, to judge whether these points correlate with the coplanar characteristics. Accordingly, the relevant point from each coplanar cluster is chosen. The relevant points are reconstructed to a triangular mesh and the error rate remains within a certain tolerance level, and significantly reducing number of calculations needed for reconstruction. The hierarchical triangular mesh based on the octree data structure is presented. This study presents hierarchical simplification and hierarchical rendering for the reconstructed model to suit user demand, and produce a uniform or feature-sensitive simplified model that facilitates rapid further mesh-based applications, especially the level of detail.