Algorithms for clustering data
Algorithms for clustering data
An introduction to computational learning theory
An introduction to computational learning theory
A new approach to the minimum cut problem
Journal of the ACM (JACM)
Inferring global perceptual contours from local features
International Journal of Computer Vision - Special issue on computer vision research at the University of Southern California
Data clustering using a model granular magnet
Neural Computation
Image segmentation from consensus information
Computer Vision and Image Understanding
Unsupervised Texture Segmentation in a Deterministic Annealing Framework
IEEE Transactions on Pattern Analysis and Machine Intelligence
An on-line agglomerative clustering method for nonstationary data
Neural Computation
Authoritative sources in a hyperlinked environment
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
A randomized algorithm for pairwise clustering
Proceedings of the 1998 conference on Advances in neural information processing systems II
Combinatorial Algorithms
Constrained Clustering as an Optimization Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Figure-Ground Discrimination: A Combinatorial Optimization Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pairwise Data Clustering by Deterministic Annealing
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Factorization Approach to Grouping
ECCV '98 Proceedings of the 5th 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)
Segmentation by Grouping Junctions
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Image Segmentation Using Local Variation
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A multi-body factorization method for motion analysis
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Segmentation Using Eigenvectors: A Unifying View
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adjustment Learning and Relevant Component Analysis
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Multivariate Saddle Point Detection for Statistical Clustering
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Data Resampling for Path Based Clustering
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Contraction kernels and combinatorial maps
Pattern Recognition Letters - Special issue: Graph-based representations in pattern recognition
Computer Vision and Image Understanding - Special issue on Face recognition
Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bagging for Path-Based Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-based image retrieval by clustering
MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
On combining graph-partitioning with non-parametric clustering for image segmentation
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalizing Swendsen-Wang to Sampling Arbitrary Posterior Probabilities
IEEE Transactions on Pattern Analysis and Machine Intelligence
More optimal strokes for NPR sketching
GRAPHITE '05 Proceedings of the 3rd international conference on Computer graphics and interactive techniques in Australasia and South East Asia
Dominant Sets and Pairwise Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Information cut for clustering using a gradient descent approach
Pattern Recognition
Fast multiscale clustering and manifold identification
Pattern Recognition
Attribute-space connectivity and connected filters
Image and Vision Computing
Randomized cuts for 3D mesh analysis
ACM SIGGRAPH Asia 2008 papers
Shape Matching by Segmentation Averaging
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Benchmarking Image Segmentation Algorithms
International Journal of Computer Vision
Hypergraph Cuts & Unsupervised Representation for Image Segmentation
Fundamenta Informaticae
Hebbian self-organizing integrate-and-fire networks for data clustering
Neural Computation
Proceedings of the 2010 conference on Information Modelling and Knowledge Bases XXI
Reestablishing consistency of uncertain geometric relations in digital images
Proceedings of the 11th international conference on Theoretical foundations of computer vision
Color image segmentation based on the normal distribution and the dynamic thresholding
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part I
Spatially coherent clustering using graph cuts
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
A new graph-theoretic approach to clustering and segmentation
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Adaptation for multiple cue integration
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Spectral graph partitioning based on a random walk diffusion similarity measure
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
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We present a stochastic clustering algorithm which uses pairwise similarity of elements and show how it can be used to address various problems in computer vision, including the low-level image segmentation, mid-level perceptual grouping, and high-level image database organization. The clustering problem is viewed as a graph partitioning problem, where nodes represent data elements and the weights of the edges represent pairwise similarities. We generate samples of cuts in this graph, by using Karger's contraction algorithm (1996), and compute an "average" cut which provides the basis for our solution to the clustering problem. The stochastic nature of our method makes it robust against noise, including accidental edges and small spurious clusters. The complexity of our algorithm is very low: O(|E| log2 N) for N objects, |E| similarity relations, and a fixed accuracy level. In addition, and without additional computational cost, our algorithm provides a hierarchy of nested partitions. We demonstrate the superiority of our method for image segmentation on a few synthetic and real images, both B&W and color. Our other examples include the concatenation of edges in a cluttered scene (perceptual grouping) and the organization of an image database for the purpose of multiview 3D object recognition