Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Trace Inference, Curvature Consistency, and Curve Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Inferring Surface Trace and Differential Structure from 3-D Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Symbolic Construction of a 2-D Scale-Space Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic 3D Models with Local and Global Deformations: Deformable Superquadrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual Organization for Scene Segmentation and Description
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
A neural model of contour integration in the primary visual cortex
Neural Computation
Inference of Integrated Surface, Curve, and Junction Descriptions From Sparse 3D Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual organization in computer vision: status, challenges, and potential
Computer Vision and Image Understanding - Special issue on perceptual organization in computer vision
A Comparison of Measures for Detecting Natural Shapes in Cluttered Backgrounds
International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
N-Dimensional Tensor Voting and Application to Epipolar Geometry Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational Framework for Segmentation and Grouping
Computational Framework for Segmentation and Grouping
Curvature-Augmented Tensor Voting for Shape Inference from Noisy 3D Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation and Measurement of the Cortex from 3D MR Images
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Layered 4D Representation and Voting for Grouping from Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Text segmentation in color images using tensor voting
Image and Vision Computing
Iterated tensor voting and curvature improvement
Signal Processing
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
Computer Vision and Image Understanding
Graph-based perceptual segmentation of stereo vision 3D images at multiple abstraction levels
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
Nonlinear Dimensionality Reduction by Topologically Constrained Isometric Embedding
International Journal of Computer Vision
A tensor voting for corrupted region inference and text image segmentation
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
An improved representation of junctions through asymmetric tensor diffusion
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
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
A maximum enhancing higher-order tensor glyph
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
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Abstract--Most computer vision applications require the reliable detection of boundaries. In the presence of outliers, missing data, orientation discontinuities, and occlusion, this problem is particularly challenging. We propose to address it by complementing the tensor voting framework, which was limited to second order properties, with first order representation and voting. First order voting fields and a mechanism to vote for 3D surface and volume boundaries and curve endpoints in 3D are defined. Boundary inference is also useful for a second difficult problem in grouping, namely, automatic scale selection. We propose an algorithm that automatically infers the smallest scale that can preserve the finest details. Our algorithm then proceeds with progressively larger scales to ensure continuity where it has not been achieved. Therefore, the proposed approach does not oversmooth features or delay the handling of boundaries and discontinuities until model misfit occurs. The interaction of smooth features, boundaries, and outliers is accommodated by the unified representation, making possible the perceptual organization of data in curves, surfaces, volumes, and their boundaries simultaneously. We present results on a variety of data sets to show the efficacy of the improved formalism.