A resource-allocating network for function interpolation
Neural Computation
A morphable model for the synthesis of 3D faces
Proceedings of the 26th 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
IEEE Transactions on Visualization and Computer Graphics
An Efficient k-Means Clustering Algorithm: Analysis and Implementation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spherical parametrization and remeshing
ACM SIGGRAPH 2003 Papers
Fundamentals of spherical parameterization for 3D meshes
ACM SIGGRAPH 2003 Papers
Multi-level partition of unity implicits
ACM SIGGRAPH 2003 Papers
Interpolating scattered data using 2D self-organizing feature maps
Graphical Models
ACM SIGGRAPH 2004 Papers
Feature-based surface parameterization and texture mapping
ACM Transactions on Graphics (TOG)
Sparse surface reconstruction with adaptive partition of unity and radial basis functions
Graphical Models - Special issue on SMI 2004
Spectral surface quadrangulation
ACM SIGGRAPH 2006 Papers
Mesh parameterization methods and their applications
Foundations and Trends® in Computer Graphics and Vision
Facial Shape-from-shading and Recognition Using Principal Geodesic Analysis and Robust Statistics
International Journal of Computer Vision
Quasi-isometric parameterization for texture mapping
Pattern Recognition
Differentials-based segmentation and parameterization for point-sampled surfaces
Journal of Computer Science and Technology
Dual-RBF based surface reconstruction
The Visual Computer: International Journal of Computer Graphics
From 3D Point Clouds to Pose-Normalised Depth Maps
International Journal of Computer Vision
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
A dynamic over-sampling procedure based on sensitivity for multi-class problems
Pattern Recognition
Hierarchically partitioned implicit surfaces for interpolating large point set models
GMP'06 Proceedings of the 4th international conference on Geometric Modeling and Processing
IEEE Transactions on Neural Networks
Reformulated radial basis neural networks trained by gradient descent
IEEE Transactions on Neural Networks
Multiscale approximation with hierarchical radial basis functions networks
IEEE Transactions on Neural Networks
Meshing point clouds using spherical parameterization
SPBG'04 Proceedings of the First Eurographics conference on Point-Based Graphics
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We propose a self-organizing Radial Basis Function (RBF) neural network method for parameterization of freeform surfaces from larger, noisy and unoriented point clouds. In particular, an adaptive sequential learning algorithm is presented for network construction from a single instance of point set. The adaptive learning allows neurons to be dynamically inserted and fully adjusted (e.g. their locations, widths and weights), according to mapping residuals and data point novelty associated to underlying geometry. Pseudo-neurons, exhibiting very limited contributions, can be removed through a pruning procedure. Additionally, a neighborhood extended Kalman filter (NEKF) was developed to significantly accelerate parameterization. Experimental results show that this adaptive learning enables effective capture of global low-frequency variations while preserving sharp local details, ultimately leading to accurate and compact parameterization, as characterized by a small number of neurons. Parameterization using the proposed RBF network provides simple, low cost and low storage solutions to many problems such as surface construction, re-sampling, hole filling, multiple level-of-detail meshing and data compression from unstructured and incomplete range data. Performance results are also presented for comparison.