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updated docs
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Davis King
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@ -52,6 +52,8 @@
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<item>max_sum_submatrix</item>
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<item>find_max_factor_graph_nmplp</item>
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<item>find_max_factor_graph_viterbi</item>
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<item>find_max_factor_graph_potts</item>
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<item>min_cut</item>
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</section>
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<section>
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@ -72,6 +74,8 @@
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<item>poly_min_extrap</item>
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<item>lagrange_poly_min_extrap</item>
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<item>line_search</item>
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<item>graph_cut_score</item>
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<item>potts_model_score</item>
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</section>
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</top>
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@ -532,6 +536,76 @@ subject to the following constraint:
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</component>
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<!-- ************************************************************************* -->
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<component>
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<name>potts_model_score</name>
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<file>dlib/graph_cuts.h</file>
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<spec_file link="true">dlib/graph_cuts/find_max_factor_graph_potts_abstract.h</spec_file>
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<description>
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This routine computes the model score for a Potts problem and a
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candidate labeling. This score is the quantity maximised
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by the <a href="#find_max_factor_graph_potts">find_max_factor_graph_potts</a>
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routine.
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</description>
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</component>
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<!-- ************************************************************************* -->
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<component>
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<name>graph_cut_score</name>
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<file>dlib/graph_cuts.h</file>
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<spec_file link="true">dlib/graph_cuts/min_cut_abstract.h</spec_file>
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<description>
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This routine computes the score for a candidate graph cut. This is the
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quantity minimized by the <a href="#min_cut">min_cut</a> algorithm.
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</description>
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</component>
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<!-- ************************************************************************* -->
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<component>
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<name>min_cut</name>
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<file>dlib/graph_cuts.h</file>
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<spec_file link="true">dlib/graph_cuts/min_cut_abstract.h</spec_file>
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<description>
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This is a function object which can be used to find the min cut
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on a graph.
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The implementation is based on the method described in the following
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paper:
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<blockquote>
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An Experimental Comparison of Min-Cut/Max-Flow Algorithms for
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Energy Minimization in Vision, by Yuri Boykov and Vladimir Kolmogorov,
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in PAMI 2004.
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</blockquote>
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</description>
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</component>
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<!-- ************************************************************************* -->
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<component>
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<name>find_max_factor_graph_potts</name>
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<file>dlib/graph_cuts.h</file>
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<spec_file link="true">dlib/graph_cuts/find_max_factor_graph_potts_abstract.h</spec_file>
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<description>
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This function is a tool for exactly solving the MAP problem in a Potts
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model. This type of model is useful when you have a problem which
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can be modeled as a bunch of binary decisions on some variables,
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but you have some kind of labeling consistency constraint. This
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means that there is some penalty for giving certain pairs of variables
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different labels. So in addition to trying to figure out how to best
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label each variable on its own, you have to worry about making the
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labels pairwise consistent in some sense. The find_max_factor_graph_potts()
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routine can be used to find the most probable/highest scoring
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labeling for this type of model.
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<p>The implementation of this routine is based on the <a href="#min_cut">min_cut</a> object.</p>
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</description>
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</component>
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<!-- ************************************************************************* -->
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<component>
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@ -73,6 +73,16 @@
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<term file="optimization.html" name="find_max_trust_region"/>
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<term file="optimization.html" name="find_max_factor_graph_nmplp"/>
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<term file="optimization.html" name="find_max_factor_graph_viterbi"/>
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<term file="optimization.html" name="find_max_factor_graph_potts"/>
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<term file="optimization.html" name="min_cut"/>
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<term file="optimization.html" name="graph_cut_score"/>
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<term file="optimization.html" name="potts_model_score"/>
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<term file="dlib/graph_cuts/min_cut_abstract.h.html" name="node_label"/>
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<term link="dlib/graph_cuts/min_cut_abstract.h.html#node_label" name="SOURCE_CUT"/>
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<term link="dlib/graph_cuts/min_cut_abstract.h.html#node_label" name="SINK_CUT"/>
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<term link="dlib/graph_cuts/min_cut_abstract.h.html#node_label" name="FREE_NODE"/>
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<term file="optimization.html" name="solve_trust_region_subproblem"/>
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<term file="optimization.html" name="find_min_single_variable"/>
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<term file="optimization.html" name="find_min_using_approximate_derivatives"/>
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@ -170,7 +180,7 @@
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<term file="algorithms.html" name="randomly_subsample"/>
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<term file="ml.html" name="select_all_distinct_labels"/>
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<term file="dlib/svm/multiclass_tools_abstract.h.html#find_missing_pairs" name="find_missing_pairs"/>
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<term file="dlib/svm/multiclass_tools_abstract.h.html" name="find_missing_pairs"/>
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<term file="ml.html" name="svm_multiclass_linear_trainer"/>
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<term link="ml.html#svm_multiclass_linear_trainer" name="Multiclass SVM"/>
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