Multivariate interpolation of large sets of scattered data
ACM Transactions on Mathematical Software (TOMS)
Volumetric shape description of range data using “Blobby Model”
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Surface reconstruction from unorganized points
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Three-dimensional alpha shapes
ACM Transactions on Graphics (TOG)
Piecewise smooth surface reconstruction
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Automatic reconstruction of surfaces and scalar fields from 3D scans
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
A volumetric method for building complex models from range images
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
A Level-Set Approach to 3D Reconstruction from Range Data
International Journal of Computer Vision
A Generalization of Algebraic Surface Drawing
ACM Transactions on Graphics (TOG)
Geometric structures for three-dimensional shape representation
ACM Transactions on Graphics (TOG)
Proceedings of the sixth ACM symposium on Solid modeling and applications
Feature sensitive surface extraction from volume data
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Reconstruction and representation of 3D objects with radial basis functions
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Estimating the in/out function of a surface represented by points
SM '03 Proceedings of the eighth ACM symposium on Solid modeling and applications
A two-dimensional interpolation function for irregularly-spaced data
ACM '68 Proceedings of the 1968 23rd ACM national conference
A Multi-scale Approach to 3D Scattered Data Interpolation with Compactly Supported Basis Functions
SMI '03 Proceedings of the Shape Modeling International 2003
Fast Surface Reconstruction Using the Level Set Method
VLSM '01 Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01)
Adaptive shape evolution using blending
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Topologically adaptable snakes
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Multi-level partition of unity implicits
ACM SIGGRAPH 2003 Papers
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
Robust moving least-squares fitting with sharp features
ACM SIGGRAPH 2005 Papers
Spectral moving removal of non-isolated surface outlier clusters
Computer-Aided Design
Robust mesh reconstruction from unoriented noisy points
2009 SIAM/ACM Joint Conference on Geometric and Physical Modeling
Topology- and error-driven extension of scalar functions from surfaces to volumes
ACM Transactions on Graphics (TOG)
Technical Section: Robust normal estimation for point clouds with sharp features
Computers and Graphics
Defining, contouring, and visualizing scalar functions on point-sampled surfaces
Computer-Aided Design
Multi-level partition of unity algebraic point set surfaces
Journal of Computer Science and Technology
SMI 2011: Full Paper: Harmonic point cloud orientation
Computers and Graphics
Removal of surface artifacts of material volume data with defects
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part II
Detail-Preserving local editing for point-sampled geometry
CGI'06 Proceedings of the 24th international conference on Advances in Computer Graphics
Robust filtering of noisy scattered point data
SPBG'05 Proceedings of the Second Eurographics / IEEE VGTC conference on Point-Based Graphics
Surface- and volume-based techniques for shape modeling and analysis
SIGGRAPH Asia 2013 Courses
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We present a novel surface reconstruction algorithm that can recover high-quality surfaces from noisy and defective data sets without any normal or orientation information. A set of new techniques are introduced to afford extra noise tolerability, robust orientation alignment, reliable outlier removal, and satisfactory feature recovery. In our algorithm, sample points are first organized by an octree. The points are then clustered into a set of monolithically singly-oriented groups. The inside/outside orientation of each group is determined through a robust voting algorithm. We locally fit an implicit quadric surface in each octree cell. The locally fitted implicit surfaces are then blended to produce a signed distance field using the modified Shepardýs method. We develop sophisticated iterative fitting algorithms to afford improved noise tolerance both in topology recognition and geometry accuracy. Furthermore, this iterative fitting algorithm, coupled with a local model selection scheme, provides a reliable sharp feature recovery mechanism even in the presence of bad input.