Boundary Detection by Constrained Optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Variational methods in image segmentation
Variational methods in image segmentation
Unsupervised Texture Segmentation in a Deterministic Annealing Framework
IEEE Transactions on Pattern Analysis and Machine Intelligence
Histogram clustering for unsupervised segmentation and image retrieval
Pattern Recognition Letters
A Variational Model for Image Classification and Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Segmentation by Data-Driven Markov Chain Monte Carlo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parametric Distributional Clustering for Image Segmentation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Bayesian extension to the language model for ad hoc information retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Bagging for Path-Based Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Cluster Preserving Embedding of Nonmetric Proximity Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stability-based validation of clustering solutions
Neural Computation
Probabilistic models of text and images
Probabilistic models of text and images
Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability)
Bayesian order-adaptive clustering for video segmentation
EMMCVPR'07 Proceedings of the 6th international conference on Energy minimization methods in computer vision and pattern recognition
Bayesian image segmentation with mean shift
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
The infinite hidden Markov random field model
IEEE Transactions on Neural Networks
Image segmentation by MAP-ML estimations
IEEE Transactions on Image Processing
Logistic Stick-Breaking Process
The Journal of Machine Learning Research
A spatially-constrained normalized Gamma process prior
Expert Systems with Applications: An International Journal
Monte Carlo cluster refinement for noise robust image segmentation
Journal of Visual Communication and Image Representation
Unsupervised classification of SAR images using normalized gamma process mixtures
Digital Signal Processing
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Image segmentation algorithms partition the set of pixels of an image into a specific number of different, spatially homogeneous groups. We propose a nonparametric Bayesian model for histogram clustering which automatically determines the number of segments when spatial smoothness constraints on the class assignments are enforced by a Markov Random Field. A Dirichlet process prior controls the level of resolution which corresponds to the number of clusters in data with a unique cluster structure. The resulting posterior is efficiently sampled by a variant of a conjugate-case sampling algorithm for Dirichlet process mixture models. Experimental results are provided for real-world gray value images, synthetic aperture radar images and magnetic resonance imaging data.