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114
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CAIP
2007
Springer
217views Image Analysis» more  CAIP 2007»
15 years 3 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...
ICIP
2009
IEEE
14 years 7 months ago
Random swap EM algorithm for finite mixture models in image segmentation
The Expectation-Maximization (EM) algorithm is a popular tool in statistical estimation problems involving incomplete data or in problems which can be posed in a similar form, suc...
Qinpei Zhao, Ville Hautamäki, Ismo Kärkk...
80
Voted
MICCAI
2000
Springer
15 years 1 months ago
Fusing Speed and Phase Information for Vascular Segmentation in Phase Contrast MR Angiograms
This paper presents a statistical approach to aggregating speed and phase (directional) information for vascular segmentation in phase contrast magnetic resonance angiograms (PC-MR...
Albert C. S. Chung, J. Alison Noble, Paul E. Summe...
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
14 years 11 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang
91
Voted
CVPR
2008
IEEE
15 years 11 months ago
Edge preserving spatially varying mixtures for image segmentation
A new hierarchical Bayesian model is proposed for image segmentation based on Gaussian mixture models (GMM) with a prior enforcing spatial smoothness. According to this prior, the...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. Ga...