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» Robust Image Segmentation with Mixtures of Student's t-Distr...
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TNN
2010
216views Management» more  TNN 2010»
13 years 29 days ago
Simplifying mixture models through function approximation
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Kai Zhang, James T. Kwok
CVPR
2008
IEEE
14 years 8 months ago
Unsupervised estimation of segmentation quality using nonnegative factorization
We propose an unsupervised method for evaluating image segmentation. Common methods are typically based on evaluating smoothness within segments and contrast between them, and the...
Roman Sandler, Michael Lindenbaum
MVA
2007
132views Computer Vision» more  MVA 2007»
13 years 7 months ago
A Robust Coarse-to-Fine Method for Pupil Localization in Non-ideal Eye Images
Pupil localization is a very important preprocessing step in many machine vision applications. Accurate and robust pupil localization especially in non-ideal eye images (such as i...
Xiaoyan Yuan, Pengfei Shi
PAMI
2007
187views more  PAMI 2007»
13 years 5 months ago
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
—A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as...
Gustavo Carneiro, Antoni B. Chan, Pedro J. Moreno,...
ICCV
2009
IEEE
13 years 4 months ago
Component analysis approach to estimation of tissue intensity distributions of 3D images
Many segmentation problems in medical imaging rely on accurate modeling and estimation of tissue intensity probability density functions. Gaussian mixture modeling, currently the ...
Arridhana Ciptadi, Cheng Chen, Vitali Zagorodnov