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Fix capitalization

This commit is contained in:
Simon Giraudot 2020-03-24 16:30:01 +01:00
parent 74f3c2564c
commit b77e138438
3 changed files with 9 additions and 9 deletions
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8
BGL/doc/BGL/BGL.txt
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@ -657,7 +657,7 @@ as shown in \ref BGL_polyhedron_3/polyhedron_partition.cpp "this example".
\section BGLGraphcut Graph Cut
An optimal partition from a set of labels can be computed through a
graph cut approach called Alpha Expansion
graph cut approach called alpha expansion
\cgalCite{Boykov2001FastApproximate}. \cgal provides
`CGAL::alpha_expansion_graphcut()` which, for a graph \f$(V,E)\f$,
computes the partition `f` that minimizes the following cost function:
@ -690,11 +690,11 @@ list_ version provides a good compromise and is therefore the default
implementation.
\cgalFigureBegin{alpha_exp, alpha_expansion.png}
Comparison of time and memory consumed by the different Alpha
Expansion implementation.
Comparison of time and memory consumed by the different alpha
expansion implementation.
\cgalFigureEnd
The following example shows how to apply the Alpha Expansion algorithm
The following example shows how to apply the alpha expansion algorithm
to a `boost::adjacency_list` describing a 2D array with 3 labels "X",
" " and "O":

6
BGL/include/CGAL/boost/graph/alpha_expansion_graphcut.h
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@ -449,8 +449,8 @@ public:
/**
\ingroup PkgBGLPartition
regularizes a partition of a graph into `n` labels using the Alpha
Expansion algorithm \cgalCite{Boykov2001FastApproximate}.
regularizes a partition of a graph into `n` labels using the alpha
expansion algorithm \cgalCite{Boykov2001FastApproximate}.
For a graph \f$(V,E)\f$, this function computes a partition `f`
that minimizes the following cost function:
@ -504,7 +504,7 @@ public:
\cgalParamEnd
\cgalParamBegin{implementation_tag}
tag used to select
which implementation of the Alpha Expansion should be
which implementation of the alpha expansion should be
used. Available implementation tags are:
- `CGAL::Alpha_expansion_boost_adjacency_list` (default)
- `CGAL::Alpha_expansion_boost_compressed_sparse_row_tag`

4
Classification/doc/Classification/Classification.txt
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@ -21,7 +21,7 @@ This component implements the algorithm described in \cgalCite{cgal:lm-clscm-12}
- a set of labels (for example: _ground_, _building_, _vegetation_) is defined by the user;
- a classifier is defined and trained: from the set of values taken by the features at an input item, it measures the likelihood of this item to belong to one label or another;
- classification is computed itemwise using the classifier;
- additional regularization can be used by smoothing either locally or globally through a _Graph Cut_ \cgalCite{Boykov2001FastApproximate} approach.
- additional regularization can be used by smoothing either locally or globally through a _graph cut_ \cgalCite{Boykov2001FastApproximate} approach.
\cgalFigureBegin{Classification_organization_fig,organization.svg}
Organization of the package.
@ -431,7 +431,7 @@ quantifies the strengh of the regularization, \f$i \sim j\f$
represents the pairs of neighboring items and
\f$\mathbf{1}_{\{.\}}\f$ the characteristic function.
A _Graph Cut_ based algorithm (Alpha Expansion) is used to quickly reach
A _graph cut_ based algorithm (alpha expansion) is used to quickly reach
an approximate solution close to the global optimum of this energy.
This method allows to consistently segment the input data set in