Surface simplification using quadric error metrics
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Appearance-preserving simplification
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Simplifying surfaces with color and texture using quadric error metrics
Proceedings of the conference on Visualization '98
MSE '02 Proceedings of the Fourth IEEE International Symposium on Multimedia Software Engineering
Shape-Adaptive 3-D Mesh Simplification Based on Local Optimality Measurement
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
An Effective Feature-Preserving Mesh Simplification Scheme Based on Face Constriction
PG '01 Proceedings of the 9th Pacific Conference on Computer Graphics and Applications
Mesh Simplification Using Four-Face Clusters
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
Technical Section: Moment-based metrics for mesh simplification
Computers and Graphics
Automatic reconstruction of B-spline surfaces with constrained boundaries
Computers and Industrial Engineering
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Surface mesh simplification is popular in many applications such as medical visualization, 3-D collaborative CAD and etc. Many effective algorithms have been proposed in recent years. However, most of them paid no attention to keep the global geometry features, which in many cases influence the approximation of simplified mesh seriously. In this paper, we present a QEM (quadric error metric) based triangle mesh simplification method, which can preserve the global geometry features of the original model efficiently. After finding all global geometry features by detecting the crease angles of two connecting faces, every edge is assigned a weight according to the relationship between it and the global geometry features. Then the QEM is modified to postpone the simplification of global geometry features by adding the assigned weight to the contraction cost of every edge. Experimental results show that our method can not only preserve the global geometry features efficiently, but also produce less simplification error than traditional edge contraction method using the QEM.