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» Markov Random Field Modeling in Computer Vision
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ICDAR
2009
IEEE
13 years 7 months ago
Unconstrained Handwritten Document Layout Extraction Using 2D Conditional Random Fields
The paper describes a new approach using a Conditional Random Fields (CRFs) to extract physical and logical layouts in unconstrained handwritten letters such as those sent by indi...
Florent Montreuil, Emmanuele Grosicki, Laurent Heu...
ECAI
2010
Springer
13 years 7 months ago
Continuous Conditional Random Fields for Regression in Remote Sensing
Conditional random fields (CRF) are widely used for predicting output variables that have some internal structure. Most of the CRF research has been done on structured classificati...
Vladan Radosavljevic, Slobodan Vucetic, Zoran Obra...
SIBGRAPI
2006
IEEE
14 years 3 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...
ECCV
2000
Springer
14 years 11 months ago
Euclidean Group Invariant Computation of Stochastic Completion Fields Using Shiftable-Twistable Functions
We describe a method for computing the likelihood that a completion joining two contour fragments passes through any given position and orientation in the image plane, that is, a m...
John W. Zweck, Lance R. Williams
MLMI
2007
Springer
14 years 3 months ago
Conditional Sequence Model for Context-Based Recognition of Gaze Aversion
Eye gaze and gesture form key conversational grounding cues that are used extensively in face-to-face interaction among people. To accurately recognize visual feedback during inter...
Louis-Philippe Morency, Trevor Darrell