CRF Model
The Binary LN Model described in the bachelor thesis "Maximum Likelihood Learning And Inference In Conditional Random Fields" by Iulian Vlad Serban, University of Copenhagen, 2012.
CRF::CRFModel_GraphCut Class Reference
Inheritance diagram for CRF::CRFModel_GraphCut:
CRF::CRFModel CRF::CRFModel_CD

List of all members.

Public Member Functions

 CRFModel_GraphCut ()
 CRFModel_GraphCut (int imgWidth, int imgHeight, int MAPSTEPS)
int_int_vector EstimateMAP (const double_double_vector Input)

Constructor & Destructor Documentation

Constructor that initializes the configuration of the model. Width and Height are set to 1 pixel.

CRFModel_GraphCut::CRFModel_GraphCut ( int  imgWidth,
int  imgHeight,
int  MAPSTEPS 
)

Constructor that initializes the configuration of the model.

Parameters:
imgWidthImage width in pixels.
imgHeightImage height in pixels.
MAPSTEPSMaximum number of steps to perform for MAP estimation. This is irrelevant for Graph Cut methods.

Member Function Documentation

int_int_vector CRFModel_GraphCut::EstimateMAP ( const double_double_vector  Input) [virtual]

Finds the MAP (Maximum Aposterori Estimation) solution using Graph Cut methods.

Parameters:
InputInput sample.
Returns:
MAP solution.

Reimplemented from CRF::CRFModel.


The documentation for this class was generated from the following files:
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