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» Modeling Image Textures by Gibbs Random Fields
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ICIP
2005
IEEE
16 years 2 months ago
Segmenting non stationary images with triplet Markov fields
The hidden Markov field (HMF) model has been used in many model-based solutions to image analysis problems, including that of image segmentation, and generally gives satisfying re...
Dalila Benboudjema, Wojciech Pieczynski
88
Voted
ECCV
2002
Springer
16 years 2 months ago
Factorial Markov Random Fields
In this paper we propose an extension to the standard Markov Random Field (MRF) model in order to handle layers. Our extension, which we call a Factorial MRF (FMRF), is analogous t...
Junhwan Kim, Ramin Zabih
ICCV
2011
IEEE
14 years 19 days ago
Decision Tree Fields
This paper introduces a new formulation for discrete image labeling tasks, the Decision Tree Field (DTF), that combines and generalizes random forests and conditional random fiel...
Sebastian Nowozin, Carsten Rother, Shai Bagon, Ban...
110
Voted
ICIP
2001
IEEE
16 years 2 months ago
Robust fast extraction of video objects combining frame differences and adaptive reference image
This paper introduces a video object segmentation algorithm developed in the context of the European project Art.live1 where constraints on the quality of segmentation and the pro...
Alice Caplier, Laurent Bonnaud, Jean-Marc Chassery
80
Voted
CVPR
2007
IEEE
16 years 2 months ago
Iterative MAP and ML Estimations for Image Segmentation
Image segmentation plays an important role in computer vision and image analysis. In this paper, the segmentation problem is formulated as a labeling problem under a probability m...
Shifeng Chen, Liangliang Cao, Jianzhuang Liu, Xiao...