Segmentation through Variable-Order Surface Fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
A comparison of local surface geometry estimation methods
Machine Vision and Applications
Methods to recover constant radius rolling ball blends in reverse engineering
Computer Aided Geometric Design
On surface normal and Gaussian curvature approximations given data sampled from a smooth surface
Computer Aided Geometric Design
A survey of methods for recovering quadrics in triangle meshes
ACM Computing Surveys (CSUR)
Curvature-Augmented Tensor Voting for Shape Inference from Noisy 3D Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimizing 3D triangulations using discrete curvature analysis
Mathematical Methods for Curves and Surfaces
Computation of Surface Geometry and Segmentation Using Covariance Techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Normal vector voting: crease detection and curvature estimation on large, noisy meshes
Graphical Models - Special issue: Processing on large polygonal meshes
Intrinsic Surface Properties from Surface Triangulation
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Estimating surface normals in noisy point cloud data
Proceedings of the nineteenth annual symposium on Computational geometry
Estimating the tensor of curvature of a surface from a polyhedral approximation
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Anisotropic polygonal remeshing
ACM SIGGRAPH 2003 Papers
Estimating differential quantities using polynomial fitting of osculating jets
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
A novel cubic-order algorithm for approximating principal direction vectors
ACM Transactions on Graphics (TOG)
Estimating Curvatures and Their Derivatives on Triangle Meshes
3DPVT '04 Proceedings of the 3D Data Processing, Visualization, and Transmission, 2nd International Symposium
Normal Based Estimation of the Curvature Tensor for Triangular Meshes
PG '04 Proceedings of the Computer Graphics and Applications, 12th Pacific Conference
Estimating the principal curvatures and the Darboux frame from real 3-D range data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Consistent computation of first- and second-order differential quantities for surface meshes
Proceedings of the 2008 ACM symposium on Solid and physical modeling
Robust Voronoi-based curvature and feature estimation
2009 SIAM/ACM Joint Conference on Geometric and Physical Modeling
Illustrative visualization: interrogating triangulated surfaces
Computing - Geometric Modelling, Dagstuhl 2008
C1 continuities detection in triangular meshes
Computer-Aided Design
SSIP '09/MIV'09 Proceedings of the 9th WSEAS international conference on signal, speech and image processing, and 9th WSEAS international conference on Multimedia, internet & video technologies
Laser scanner technology for complex surveying structures
WSEAS Transactions on Signal Processing
Voronoi-Based extraction of a feature skeleton from noisy triangulated surfaces
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Curvature tensor computation by piecewise surface interpolation
Computer-Aided Design
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Accurate curvature estimation in discrete surfaces is an important problem with numerous applications. Curvature is an indicator of ridges and can be used in applications such as shape analysis and recognition, object segmentation, adaptive smoothing, anisotropic fairing of irregular meshes, and anisotropic texture mapping. In this paper, a new framework is proposed for accurate curvature estimation in discrete surfaces. The proposed framework is based on a local directional curve sampling of the surface where the sampling frequency can be controlled. This local model has a large number of degrees of freedoms compared with known techniques and, so, can better represent the local geometry. The proposed framework is quantitatively evaluated and compared with common techniques for surface curvature estimation. In order to perform an unbiased evaluation in which smoothing effects are factored out, we use a set of randomly generated Bezier surface patches for which the curvature values can be analytically computed. It is demonstrated that, through the establishment of sampling conditions, the error in estimations obtained by the proposed framework is smaller and that the proposed framework is less sensitive to low sampling density, sampling irregularities, and sampling noise.