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CVPR
1999
IEEE
14 years 7 months ago
Histogram Clustering for Unsupervised Image Segmentation
This paper introduces a novel statistical mixture model for probabilistic grouping of distributional histogram data. Adopting the Bayesian framework, we propose to perform anneale...
Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann
DAGM
1998
Springer
13 years 9 months ago
Discrete Mixture Models for Unsupervised Image Segmentation
This paper introduces a novel statistical mixture model for probabilistic clustering of histogram data and, more generally, for the analysis of discrete co occurrence data. Adoptin...
Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann
ICIP
2002
IEEE
14 years 6 months ago
Unsupervised image segmentation via Markov trees and complex wavelets
The goal in image segmentation is to label pixels in an image based on the properties of each pixel and its surrounding region. Recently Content-Based Image Retrieval (CBIR) has e...
Cián W. Shaffrey, Ian Jermyn, Nick G. Kings...
TIP
2002
179views more  TIP 2002»
13 years 4 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki
CVIU
2006
166views more  CVIU 2006»
13 years 5 months ago
Non-parametric and light-field deformable models
Statistical shape-and-texture appearance models use image morphing to define a rich, compact representation of object appearance. They are useful in a variety of applications incl...
Chris Mario Christoudias, Louis-Philippe Morency, ...