A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Three-dimensional object recognition from single two-dimensional images
Artificial Intelligence
Two-dimensional, model-based, boundary matching using footprints
International Journal of Robotics Research
Trace Inference, Curvature Consistency, and Curve Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Perceptual Organization to Extract 3D Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object recognition by computer: the role of geometric constraints
Object recognition by computer: the role of geometric constraints
Computer vision needs more experiments and applications
CVGIP: Image Understanding
Space and Time Bounds on Indexing 3D Models from 2D Images
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part I
Perceptual Organization for Scene Segmentation and Description
IEEE Transactions on Pattern Analysis and Machine Intelligence
The use of perceptual organization in the prediction of geometric structures
Pattern Recognition Letters
Finding convex edge groupings in an image
International Journal of Computer Vision
Object discrimination based on depth-from-occlusion
Neural Computation
Identifying salient circular arcs on curves
CVGIP: Image Understanding
Trackability as a cue for potential obstacle identification and 3-D description
International Journal of Computer Vision
A Bayesian multiple-hypothesis approach to edge grouping and contour segmentation
International Journal of Computer Vision
The role of saliency and error propagation in visual object recognition
The role of saliency and error propagation in visual object recognition
Perceptual Organization and Visual Recognition
Perceptual Organization and Visual Recognition
Generic Object Recognition: Building and Matching Coarse Descriptions from Line Drawings
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Figure-Ground Discrimination: A Combinatorial Optimization Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multidimensional Indexing for Recognizing Visual Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data and Model-Driven Selection using Color Regions
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Using Invariance and Quasi-Invariance for the Segmentation and Recovery of Curved Objects
Proceedings of the Second Joint European - US Workshop on Applications of Invariance in Computer Vision
Recognition using region correspondences
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Grouping for Recognition
What Makes a Good Feature?
Region-Based Feature Interpretation for Recognizing 3-D Models in 2-D Images
Region-Based Feature Interpretation for Recognizing 3-D Models in 2-D Images
Recognizing 3-D Objects Using 2-D Images
Recognizing 3-D Objects Using 2-D Images
Image Chunking: Defining Spatial Building Blocks for Scene Analysis
Image Chunking: Defining Spatial Building Blocks for Scene Analysis
A Framework for Performance Characterization of Intermediate-Level Grouping Modules
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Generic Grouping Algorithm and Its Quantitative Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition Using Region Correspondences
International Journal of Computer Vision
Efficient Invariant Representations
International Journal of Computer Vision
Fundamental Limits of Bayesian Inference: Order Parameters and Phase Transitions for Road Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction: Computer Vision Research at NECI
International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
3-D to 2-D Pose Determination with Regions
International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour and Texture Analysis for Image Segmentation
International Journal of Computer Vision
A General Method for Geometric Feature Matching and Model Extraction
International Journal of Computer Vision
On the Performance of Connected Components Grouping
International Journal of Computer Vision
Perceptual organization with image formation compatibilities
Pattern Recognition Letters
Perceptual organization based computational model for robust segmentation of moving objects
Computer Vision and Image Understanding
A General Method for Feature Matching and Model Extraction
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Bayesian A* Tree Search with Expected O(N) Convergence Rates for Road Tracking
EMMCVPR '99 Proceedings of the Second International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
A Continuous Shape Descriptor by Orientation Diffusion
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Design Considerations for Generic Grouping in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding Perceptually Closed Paths in Sketches and Drawings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning to Form Large Groups of Salient Image Features
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Shape from Equal Thickness Contours
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Perceptual Grouping by Selection of a Logically Minimal Model
International Journal of Computer Vision
Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object-level structured contour map extraction
Computer Vision and Image Understanding
Concatenate feature extraction for robust 3D elliptic object localization
Proceedings of the 2004 ACM symposium on Applied computing
Some General Grouping Principles: Line Perception from Points as an Example
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Multivariate image analysis in biomedicine
Journal of Biomedical Informatics
Salient Closed Boundary Extraction with Ratio Contour
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision and Image Understanding
Salient feature extraction of industrial objects for an automated assembly system
Computers in Industry - Special issue: Machine vision
Global Detection of Salient Convex Boundaries
International Journal of Computer Vision
Qualitative part-based models in content-based image retrieval
Machine Vision and Applications
Groups of Adjacent Contour Segments for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual-based region extraction from hand drawn sketches
ACST'07 Proceedings of the third conference on IASTED International Conference: Advances in Computer Science and Technology
Enhancing Boundary Primitives Using a Multiscale Quadtree Segmentation
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Shape Extraction through Region-Contour Stitching
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
An Integrated Method for Multiple Object Detection and Localization
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Detection of unexpected multi-part objects from segmented contour maps
Pattern Recognition
Computer Vision and Image Understanding
Salient feature extraction of industrial objects for an automated assembly system
Computers in Industry
A new contour corner detector based on curvature scale space
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
Optimal contour closure by superpixel grouping
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Contour grouping and abstraction using simple part models
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Review article: Edge and line oriented contour detection: State of the art
Image and Vision Computing
Spatiotemporal contour grouping using abstract part models
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Inference and Learning with Hierarchical Shape Models
International Journal of Computer Vision
Convexity grouping of salient contours
GbRPR'11 Proceedings of the 8th international conference on Graph-based representations in pattern recognition
New algorithm for segmentation of images represented as hypergraph hexagonal-grid
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Contour grouping: focusing on image patches around edges
VSMM'06 Proceedings of the 12th international conference on Interactive Technologies and Sociotechnical Systems
Object detection by contour segment networks
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Optimal Image and Video Closure by Superpixel Grouping
International Journal of Computer Vision
Hi-index | 0.15 |
This paper describes an algorithm that robustly locates salient convex collections of line segments in an image. The algorithm is guaranteed to find all convex sets of line segments in which the length of the gaps between segments is smaller than some fixed proportion of the total length of the lines. This enables the algorithm to find convex groups whose contours are partially occluded or missing due to noise. We give an expected case analysis of the algorithm's performance. This demonstrates that salient convexity is unlikely to occur at random, and hence is a strong clue that grouped line segments reflect underlying structure in the scene. We also show that our algorithm's run time is O(n2 log(n) + nm), when we wish to find the m most salient groups in an image with n line segments. We support this analysis with experiments on real data, and demonstrate the grouping system as part of a complete recognition system.