Dynamic 3D Models with Local and Global Deformations: Deformable Superquadrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Surface reconstruction from unorganized points
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
An efficient volumetric method for building closed triangular meshes from 3-D image and point data
Proceedings of the conference on Graphics interface '97
Inference of Surfaces, 3D Curves, and Junctions from Sparse, Noisy, 3D Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to algorithms
Building 3-D Human Face Models from Two Photographs
Journal of VLSI Signal Processing Systems - Special issue on multimedia signal processing
N-Dimensional Tensor Voting and Application to Epipolar Geometry Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of methods for recovering quadrics in triangle meshes
ACM Computing Surveys (CSUR)
Inference of Segmented Overlapping Surfaces from Binocular Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Curvature-Augmented Tensor Voting for Shape Inference from Noisy 3D Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconstructing Surfaces by Volumetric Regularization Using Radial Basis Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Application of the Tensor Voting Technique for Perceptual Grouping to Grey-Level Images
Proceedings of the 24th DAGM Symposium on Pattern Recognition
First Order Augmentation to Tensor Voting for Boundary Inference and Multiscale Analysis in 3D
IEEE Transactions on Pattern Analysis and Machine Intelligence
Amodal volume completion: 3D visual completion
Computer Vision and Image Understanding
Stereo Using Monocular Cues within the Tensor Voting Framework
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Surface Reconstruction using Generalized Coulomb Potentials
IEEE Transactions on Visualization and Computer Graphics
Curvature Estimation and Curve Inference with Tensor Voting: A New Approach
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Amodal volume completion: 3D visual completion
Computer Vision and Image Understanding
Efficient surface reconstruction from noisy data using regularized membrane potentials
IEEE Transactions on Image Processing
Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting
The Journal of Machine Learning Research
Tracking by cluster analysis of feature points and multiple particle filters
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
A surface reconstruction method for highly noisy point clouds
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
Efficient surface reconstruction from noisy data using regularized membrane potentials
EUROVIS'06 Proceedings of the Eighth Joint Eurographics / IEEE VGTC conference on Visualization
Surface reconstruction from noisy point clouds using coulomb potentials
VG'07 Proceedings of the Sixth Eurographics / Ieee VGTC conference on Volume Graphics
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We are interested in descriptions of 3D data sets, as obtained from stereo or a 3D digitizer. We therefore consider as input a sparse set of points, possibly associated with certain orientation information. In this paper, we address the problem of inferring integrated high-level descriptions such as surfaces, 3D curves, and junctions from a sparse point set. While the method proposed by Guy and Medioni provides excellent results for smooth structures, it only detects surface orientation discontinuities but does not localize them. For precise localization, we propose a noniterative cooperative algorithm in which surfaces, curves, and junctions work together: Initial estimates are computed based on the work by Guy and Medioni, where each point in the given sparse and possibly noisy point set is convolved with a predefined vector mask to produce dense saliency maps. These maps serve as input to our novel extremal surface and curve algorithms for initial surface and curve extraction. These initial features are refined and integrated by using excitatory and inhibitory fields. Consequently, intersecting surfaces (resp. curves) are fused precisely at their intersection curves (resp. junctions). Results on several synthetic as well as real data sets are presented.