Computing vertex normals from polygonal facets
Journal of Graphics Tools
Weights for computing vertex normals from facet normals
Journal of Graphics Tools
Optimal triangulation and quadric-based surface simplification
Computational Geometry: Theory and Applications - Special issue on multi-resolution modelling and 3D geometry compression
Virtual prototyping of solid propellant rockets
Computing in Science and Engineering
On surface normal and Gaussian curvature approximations given data sampled from a smooth surface
Computer Aided Geometric Design
I3D '01 Proceedings of the 2001 symposium on Interactive 3D graphics
Geometry and topology for mesh generation
Geometry and topology for mesh generation
A survey of methods for recovering quadrics in triangle meshes
ACM Computing Surveys (CSUR)
Scientific Computing
Computational Framework for Segmentation and Grouping
Computational Framework for Segmentation and Grouping
Estimating the tensor of curvature of a surface from a polyhedral approximation
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Mesh Generation: Application to Finite Elements
Mesh Generation: Application to Finite Elements
Continuous Shading of Curved Surfaces
IEEE Transactions on Computers
Parallel simulation of multicomponent systems
VECPAR'04 Proceedings of the 6th international conference on High Performance Computing for Computational Science
Identification of C1 and C2 discontinuities for surface meshes in CAD
Computer-Aided Design
C1 continuities detection in triangular meshes
Computer-Aided Design
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We present a parallel approach for optimizing surface meshes by redistributing vertices on a feature-aware higher-order reconstruction of a triangulated surface. Our method is based on a novel extension of the fundamental quadric, called the medial quadric. This quadric helps solve some basic geometric problems, including detection of ridges and corners, computation of one-sided normals along ridges, and construction of higher-order approximations of triangulated surfaces. Our new techniques are easy to parallelize and hence are particularly beneficial for large-scale applications.