A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Separating figure from ground with a Boltzmann machine
Vision, brain, and cooperative computation
Visual reconstruction
Trace Inference, Curvature Consistency, and Curve Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparison of the Efficiency of Deterministic and Stochastic Algorithms for Visual Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parallel and Deterministic Algorithms from MRFs: Surface Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Classifiers by Mixed Adaptation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A common framework for image segmentation
International Journal of Computer Vision
Image processing by simulated annealing
IBM Journal of Research and Development - High-density magnetic recording
Tree Approximations to Markov Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust and Efficient Detection of Salient Convex Groups
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Generic Grouping Algorithm and Its Quantitative Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extracting Salient Curves from Images: An Analysis of the Saliency Network
International Journal of 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
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
On the Performance of Connected Components Grouping
International Journal of Computer Vision
Evolutionary Approaches to Figure-Ground Separation
Applied Intelligence
Solving a Real World Assignment Problem with a Metaheuristic
Journal of Heuristics
Finding and Labeling the Subject of a Captioned Depictive Natural Photograph
IEEE Transactions on Knowledge and Data Engineering
Perceptual organization based computational model for robust segmentation of moving objects
Computer Vision and Image Understanding
A Probabilistic Interpretation of the Saliency Network
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Image Labeling and Grouping by Minimizing Linear Functionals over Cones
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
A Markov Process Using Curvature for Filtering Curve Images
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Convex Relaxations for Binary Image Partitioning and Perceptual Grouping
Proceedings of the 23rd DAGM-Symposium on Pattern Recognition
Sketches with Curvature: The Curve Indicator Random Field and Markov Processes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation of Multiple Salient Closed Contours from Real Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Path-Based Clustering for Grouping of Smooth Curves and Texture Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Euler Spiral for Shape Completion
International Journal of Computer Vision - Special Issue on Computational Vision at Brown University
Learning to Form Large Groups of Salient Image Features
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Ground from Figure Discrimination
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Figure-ground separation by a neural dynamical system
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
Comments on "ground from figure discrimination"
Pattern Recognition Letters
Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improving spatial locality of programs via data mining
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Salient Closed Boundary Extraction with Ratio Contour
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Trained Spin-Glass Model for Grouping of Image Primitives
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Competitive-Layer Model for Feature Binding and Sensory Segmentation
Neural Computation
Qualitative part-based models in content-based image retrieval
Machine Vision and Applications
Computer Vision and Image Understanding
Enhancing Boundary Primitives Using a Multiscale Quadtree Segmentation
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Proximity Graphs Based Multi-scale Image Segmentation
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Foundations of implementing the competitive layer model by Lotka-Volterra recurrent neural networks
IEEE Transactions on Neural Networks
Recovering Occlusion Boundaries from an Image
International Journal of Computer Vision
Perceptual grouping using hypercolumnar relaxation phase labeling
SSIP'05 Proceedings of the 5th WSEAS international conference on Signal, speech and image processing
Computational-geometry approach to digital image contour extraction
Transactions on computational science XIII
Selective attention guided perceptual grouping model
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
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The figure-ground discrimination problem is considered from a combinatorial optimization perspective. A mathematical model encoding the figure-ground discrimination problem that makes explicit a definition of shape based on cocircularity, smoothness, proximity, and contrast is presented. This model consists of building a cost function on the basis of image element interactions. This cost function fits the constraints of an interacting spin system that, in turn, is a well suited physical model that solves hard combinatorial optimization problems. Two combinatorial optimization methods for solving the figure-ground problem, namely mean field annealing, which combines mean field approximation theory and annealing, and microcanonical annealing, are discussed. Mean field annealing may be viewed as a deterministic approximation of stochastic methods such as simulated annealing. The theoretical bases of these methods are described, and the computational models are derived. The efficiencies of mean field annealing, simulated annealing, and microcanonical annealing algorithms are compared. Within the framework of such a comparison, the figure-ground problem may be viewed as a benchmark.