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» Discrete Mixture Models for Unsupervised Image Segmentation
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ACCV
2009
Springer
14 years 2 months ago
Levels of Details for Gaussian Mixture Models
Mixtures of Gaussians are a crucial statistical modeling tool at the heart of many challenging applications in computer vision and machine learning. In this paper, we first descri...
Vincent Garcia, Frank Nielsen, Richard Nock
SIBGRAPI
2006
IEEE
14 years 1 months ago
Improving 2D mesh image segmentation with Markovian Random Fields
Traditional mesh segmentation methods normally operate on geometrical models with no image information. On the other hand, 2D image-based mesh generation and segmentation counterp...
Alex Jesus Cuadros-Vargas, Leandro C. Gerhardinger...
ICIP
2007
IEEE
14 years 9 months ago
A Multi-Layer MRF Model for Object-Motion Detection in Unregistered Airborne Image-Pairs
In this paper, we give a probabilistic model for automatic change detection on airborne images taken with moving cameras. To ensure robustness, we adopt an unsupervised coarse mat...
Csaba Benedek, Tamas Sziranyi, Zoltan Kato, and Jo...
CVPR
1999
IEEE
1071views Computer Vision» more  CVPR 1999»
14 years 9 months ago
Adaptive Background Mixture Models for Real-Time Tracking
A common method for real-time segmentation of moving regions in image sequences involves "background subtraction," or thresholding the error between an estimate of the i...
Chris Stauffer, W. Eric L. Grimson
ICPR
2004
IEEE
14 years 8 months ago
A Variational Approach for Color Image Segmentation
In this paper we use a variational Bayesian framework for color image segmentation. Each image is represented in the L*u*v color coordinate system before being segmented by the va...
Nikolaos Nasios, Adrian G. Bors