QEM-based mesh simplification with global geometry features preserved
Proceedings of the 2nd international conference on Computer graphics and interactive techniques in Australasia and South East Asia
Robust Feature Detection and Local Classification for Surfaces Based on Moment Analysis
IEEE Transactions on Visualization and Computer Graphics
A digital mock-up visualization system capable of processing giga-scale CAD models
Computer-Aided Design
A roughness measure for 3D mesh visual masking
Proceedings of the 4th symposium on Applied perception in graphics and visualization
Adaptive Model Simplification in Real-Time Rendering for Visualization
Journal of Visualization
A local roughness measure for 3D meshes and its application to visual masking
ACM Transactions on Applied Perception (TAP)
User-assisted simplification method for triangle meshes preserving boundaries
Computer-Aided Design
Mesh simplification algorithm based on n-edge mesh collapse
ICAT'06 Proceedings of the 16th international conference on Advances in Artificial Reality and Tele-Existence
| Hi-index | 0.00 |
A new mesh simplification scheme that uses the face constriction process is presented. By introducing a statistical measure that can distinguish triangles having vertices of high local roughness from triangles in flat regions into our weight-ordering equation, along with other heuristics, our scheme can better preserve visually important features in the original mesh. To improve the shape quality of triangles, we adopt non-linear face area sensitivity in the weight ordering. Learning and feedback mechanism is also utilized to enhance user controllability. The computations are simple, making our scheme time-effective and easy to implement. In addition to comparing our scheme with other mesh simplification algorithms empirically, we compare their perform-ances by establishing a unifying ground among three basic simplification processes - decimate vertex, collapse edge, and constrict face. This unification allows us to analyze the intrinsic merits and demerits of simplification algorithms to help users make better selections.