Matrix analysis
Three-dimensional object recognition from single two-dimensional images
Artificial Intelligence
Learning optimal discriminant functions through a cooperative game of automata
IEEE Transactions on Systems, Man and Cybernetics
Probabilistic reasoning in intelligent systems: networks of plausible inference
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Learning automata: an introduction
Learning automata: an introduction
Using Perceptual Organization to Extract 3D Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Partitioning sparse matrices with eigenvectors of graphs
SIAM Journal on Matrix Analysis and Applications
The Combinatorics of Heuristic Search Termination for Object Recognition in Cluttered Environments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Space and Time Bounds on Indexing 3D Models from 2D Images
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Human and machine vision: computing perceptual organisation
Human and machine vision: computing perceptual organisation
Feature-based correspondence: an eigenvector approach
Image and Vision Computing - Special issue: BMVC 1991
Modeling hypergraphs by graphs with the same mincut properties
Information Processing Letters
Organizing Large Structural Modelbases
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust and Efficient Detection of Salient Convex Groups
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual completion of occluded surfaces
Computer Vision and Image Understanding
Inferring global perceptual contours from local features
International Journal of Computer Vision - Special issue on computer vision research at the University of Southern California
Parameter Estimation for Optimal Object Recognition: Theory andApplication
International Journal of Computer Vision
A Framework for Performance Characterization of Intermediate-Level Grouping Modules
IEEE Transactions on Pattern Analysis and Machine Intelligence
Closed-Loop Object Recognition Using Reinforcement Learning
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A Generic Grouping Algorithm and Its Quantitative Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Image Segmentation—Part I: Detection of Regular Curves in a Vector Graph
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Quantitative measures of change based on feature organization: eigenvalues and eigenvectors
Computer Vision and Image Understanding
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Figure-Ground Discrimination: A Combinatorial Optimization Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning and Feature Selection in Stereo Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Learning Texture Discrimination Rules in a Multiresolution System
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric Primitive Extraction Using a Genetic Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Compatibility Coefficients for Relaxation Labeling Processes
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ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Normalized Cuts and Image Segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Quantitative Measures of Change based on Feature Organization: Eigenvalues and Eigenvectors
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Learning to Form Large Groups of Salient Image Features
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Modeling Object Recognition as a Markov Decision Process
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume IV-Volume 7472 - Volume 7472
A distributed probabilistic system for adaptive regulation of image processing parameters
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A Hierarchical Framework for Spectral Correspondence
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
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
Improved Rooftop Detection in Aerial Images with Machine Learning
Machine Learning
Incremental learning with partial instance memory
Artificial Intelligence
On combining graph-partitioning with non-parametric clustering for image segmentation
Computer Vision and Image Understanding
Salient Closed Boundary Extraction with Ratio Contour
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spectral and meta-heuristic algorithms for software clustering
Journal of Systems and Software - Special issue: Software reverse engineering
Isoperimetric Graph Partitioning for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph Partitioning Active Contours (GPAC) for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Random Walks for Image Segmentation
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
A Neural Network Based Framework for Directional Primitive Extraction
Neural Processing Letters
Mean shift spectral clustering
Pattern Recognition
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ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Stable Image Descriptions Using Gestalt Principles
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Learning probabilistic structure to group image edges for object extraction
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
A team of continuous-action learning automata for noise-tolerant learning of half-spaces
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Perceptual organization of directional primitives using a pseudocolor hough transform
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Certainty measure of pairwise line segment perceptual relations using fuzzy logic
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Faster graph-theoretic image processing via small-world and quadtree topologies
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Learning to segment images using region-based perceptual features
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Review article: Edge and line oriented contour detection: State of the art
Image and Vision Computing
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International Journal of Computer Vision
Man-made structure detection in natural images using a causal multiscale random field
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Character segmentation for license plate recognition by K-means algorithm
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing - Volume Part II
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DAGM'06 Proceedings of the 28th conference on Pattern Recognition
Semidefinite clustering for image segmentation with a-priori knowledge
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Mathematical and Computer Modelling: An International Journal
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CISIM'12 Proceedings of the 11th IFIP TC 8 international conference on Computer Information Systems and Industrial Management
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ICVS'13 Proceedings of the 9th international conference on Computer Vision Systems
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Perceptual organization offers an elegant framework to group low-level features that are likely to come from a single object. We offer a novel strategy to adapt this grouping process to objects in a domain. Given a set of training images of objects in context, the associated learning process decides on the relative importance of the basic salient relationships such as proximity, parallelness, continuity, junctions, and common region toward segregating the objects from the background. The parameters of the grouping process are cast as probabilistic specifications of Bayesian networks that need to be learned. This learning is accomplished using a team of stochastic automata in an N-player cooperative game framework. The grouping process, which is based on graph partitioning is, able to form large groups from relationships defined over a small set of primitives and is fast. We statistically demonstrate the robust performance of the grouping and the learning frameworks on a variety of real images. Among the interesting conclusions are the significant role of photometric attributes in grouping and the ability to form large salient groups from a set of local relations, each defined over a small number of primitives.