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IEEE Transactions on Pattern Analysis and Machine Intelligence
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
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Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
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A signal processing approach to fair surface design
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Surface simplification using quadric error metrics
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
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Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Anisotropic geometric diffusion in surface processing
Proceedings of the conference on Visualization '00
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Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Dual contouring of hermite data
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Interactive geometry remeshing
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Anisotropic diffusion of surfaces and functions on surfaces
ACM Transactions on Graphics (TOG)
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SMI '99 Proceedings of the International Conference on Shape Modeling and Applications
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ACM SIGGRAPH 2003 Papers
ACM SIGGRAPH 2003 Papers
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ACM SIGGRAPH 2004 Papers
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ACM SIGGRAPH 2004 Papers
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ACM SIGGRAPH 2004 Papers
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ACM SIGGRAPH 2005 Papers
ACM SIGGRAPH 2005 Papers
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CAD-CG '05 Proceedings of the Ninth International Conference on Computer Aided Design and Computer Graphics
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Computer-Aided Design
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Computational Mechanics
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This paper presents a global optimization operator for arbitrary meshes. The global optimization operator is composed of two main terms, one part is the global Laplacian operator of the mesh which keeps the fairness and another is the constraint condition which reserves the fidelity to the mesh. The global optimization operator is formulated as a quadratic optimization problem, which is easily solved by solving a sparse linear system. Our global mesh optimization approach can be effectively used in at least three applications: smoothing the noisy mesh, improving the simplified mesh, and geometric modeling with subdivision-connectivity. Many experimental results are presented to show the applicability and flexibility of the approach.