An adaptive subdivision method for surface-fitting from sampled data
SIGGRAPH '86 Proceedings of the 13th annual conference on Computer graphics and interactive techniques
Radial basis functions for multivariable interpolation: a review
Algorithms for approximation
Mathematical elements for computer graphics (2nd ed.)
Mathematical elements for computer graphics (2nd ed.)
Surface reconstruction from unorganized points
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Curve and surface fitting with splines
Curve and surface fitting with splines
Fundamentals of computer aided geometric design
Fundamentals of computer aided geometric design
Topology representing networks
Neural Networks
Surface fitting with hierarchical splines
ACM Transactions on Graphics (TOG)
A volumetric method for building complex models from range images
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Self-organizing maps
Reconstruction and representation of 3D objects with radial basis functions
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Data Structures, Algorithms, & Software Principles in C
Data Structures, Algorithms, & Software Principles in C
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Computer Graphics
Smooth approximation and rendering of large scattered data sets
Proceedings of the conference on Visualization '01
Scattered Data Interpolation with Multilevel B-Splines
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
Scattered Data Techniques for Surfaces
Dagstuhl '97, Scientific Visualization
RBF neural network based on particle swarm optimization
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
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Many computer-aided design, computer graphics, and data visualization applications require freeform surfaces to be created from irregularly spaced and unorganized digitized data. Most surface interpolation and approximation techniques require information about the connectivity between these measured points. In contrast, the scattered data interpolation method described in this paper exploits the topological structure and unsupervised learning algorithm of a 2D self-organizing feature map (SOFM) to iteratively create a polygonal surface mesh that takes the general shape of the underlying object. The mesh representation, with quadrilateral elements, can be used to produce a facetted surface model for direct visualization or provide the means to "parametrize" the scattered data prior to generating a smooth continuous surface. Several illustrative examples using scattered range data are provided to demonstrate the data interpolation and surface reconstruction capability of the proposed 2D SOFM.