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JMIV
2010
87views more  JMIV 2010»
13 years 3 months ago
Spatially Varying Mixtures Incorporating Line Processes for Image Segmentation
Giorgos Sfikas, Christophoros Nikou, Nikolas P. Ga...
MICCAI
2008
Springer
14 years 6 months ago
MR Brain Tissue Classification Using an Edge-Preserving Spatially Variant Bayesian Mixture Model
In this paper, a spatially constrained mixture model for the segmentation of MR brain images is presented. The novelty of this work is a new, edge preserving, smoothness prior whic...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. ...
CVPR
2010
IEEE
14 years 1 months ago
A Spatially Varying PSF-based Prior for Alpha Matting
In this paper we considerably improve on a state-of-theart alpha matting approach by incorporating a new prior which is based on the image formation process. In particular, we mod...
Christoph Rhemann, Carsten Rother, Pushmeet Kohli,...
MICCAI
2005
Springer
14 years 5 months ago
Tissue Classification of Noisy MR Brain Images Using Constrained GMM
We present an automated algorithm for tissue segmentation of noisy, low contrast magnetic resonance (MR) images of the brain. We use a mixture model composed of a large number of G...
Amit Ruf, Hayit Greenspan, Jacob Goldberger
CAIP
2007
Springer
217views Image Analysis» more  CAIP 2007»
13 years 11 months ago
Mixture Models Based Background Subtraction for Video Surveillance Applications
— Background subtraction is a method commonly used to segment objects of interest in image sequences. By comparing new frames to a background model, regions of interest can be fo...
Chris Poppe, Gaëtan Martens, Peter Lambert, R...