diff --git a/docs/docs/optimization.xml b/docs/docs/optimization.xml index 8b31cac27..574e21991 100644 --- a/docs/docs/optimization.xml +++ b/docs/docs/optimization.xml @@ -52,6 +52,8 @@ max_sum_submatrix find_max_factor_graph_nmplp find_max_factor_graph_viterbi + find_max_factor_graph_potts + min_cut
@@ -72,6 +74,8 @@ poly_min_extrap lagrange_poly_min_extrap line_search + graph_cut_score + potts_model_score
@@ -532,6 +536,76 @@ subject to the following constraint: + + + + potts_model_score + dlib/graph_cuts.h + dlib/graph_cuts/find_max_factor_graph_potts_abstract.h + + This routine computes the model score for a Potts problem and a + candidate labeling. This score is the quantity maximised + by the find_max_factor_graph_potts + routine. + + + + + + + + graph_cut_score + dlib/graph_cuts.h + dlib/graph_cuts/min_cut_abstract.h + + This routine computes the score for a candidate graph cut. This is the + quantity minimized by the min_cut algorithm. + + + + + + + + min_cut + dlib/graph_cuts.h + dlib/graph_cuts/min_cut_abstract.h + + This is a function object which can be used to find the min cut + on a graph. + The implementation is based on the method described in the following + paper: +
+ An Experimental Comparison of Min-Cut/Max-Flow Algorithms for + Energy Minimization in Vision, by Yuri Boykov and Vladimir Kolmogorov, + in PAMI 2004. +
+
+ +
+ + + + + find_max_factor_graph_potts + dlib/graph_cuts.h + dlib/graph_cuts/find_max_factor_graph_potts_abstract.h + + This function is a tool for exactly solving the MAP problem in a Potts + model. This type of model is useful when you have a problem which + can be modeled as a bunch of binary decisions on some variables, + but you have some kind of labeling consistency constraint. This + means that there is some penalty for giving certain pairs of variables + different labels. So in addition to trying to figure out how to best + label each variable on its own, you have to worry about making the + labels pairwise consistent in some sense. The find_max_factor_graph_potts() + routine can be used to find the most probable/highest scoring + labeling for this type of model. +

The implementation of this routine is based on the min_cut object.

+
+ +
+ diff --git a/docs/docs/term_index.xml b/docs/docs/term_index.xml index fad85d7ab..d872b7c5d 100644 --- a/docs/docs/term_index.xml +++ b/docs/docs/term_index.xml @@ -73,6 +73,16 @@ + + + + + + + + + + @@ -170,7 +180,7 @@ - +