Point Cloud Library (PCL)
1.10.0
pcl
segmentation
random_walker.h
1
/*
2
* Software License Agreement (BSD License)
3
*
4
* Point Cloud Library (PCL) - www.pointclouds.org
5
* Copyright (c) 2012-, Open Perception, Inc.
6
*
7
* All rights reserved.
8
*
9
* Redistribution and use in source and binary forms, with or without
10
* modification, are permitted provided that the following conditions
11
* are met:
12
*
13
* * Redistributions of source code must retain the above copyright
14
* notice, this list of conditions and the following disclaimer.
15
* * Redistributions in binary form must reproduce the above
16
* copyright notice, this list of conditions and the following
17
* disclaimer in the documentation and/or other materials provided
18
* with the distribution.
19
* * Neither the name of Willow Garage, Inc. nor the names of its
20
* contributors may be used to endorse or promote products derived
21
* from this software without specific prior written permission.
22
*
23
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
24
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
25
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
26
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
27
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
28
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
29
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
30
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
31
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
32
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
33
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
34
* POSSIBILITY OF SUCH DAMAGE.
35
*
36
*/
37
38
#pragma once
39
40
#include <boost/graph/adjacency_list.hpp>
41
#include <boost/graph/graph_concepts.hpp>
42
#include <boost/concept/assert.hpp>
43
44
#include <Eigen/Dense>
45
46
namespace
pcl
47
{
48
49
namespace
segmentation
50
{
51
52
/** \brief Multilabel graph segmentation using random walks.
53
*
54
* This is an implementation of the algorithm described in "Random Walks
55
* for Image Segmentation" by Leo Grady.
56
*
57
* Given a weighted undirected graph and a small number of user-defined
58
* labels this algorithm analytically determines the probability that a
59
* random walker starting at each unlabeled vertex will first reach one
60
* of the prelabeled vertices. The unlabeled vertices are then assigned
61
* to the label for which the greatest probability is calculated.
62
*
63
* The input is a BGL graph, a property map that associates a weight to
64
* each edge of the graph, and a property map that contains initial
65
* vertex colors (the term "color" is used interchangeably with "label").
66
*
67
* \note The colors of unlabeled vertices should be set to 0, the colors
68
* of labeled vetices could be any positive numbers.
69
*
70
* \note This is the responsibility of the user to make sure that every
71
* connected component of the graph has at least one colored vertex. If
72
* the user failed to do so, then the behavior of the algorithm is
73
* undefined, i.e. it may or may not succeed, and also may or may not
74
* report failure.
75
*
76
* The output of the algorithm (i.e. label assignment) is written back
77
* to the color map.
78
*
79
* \param[in] graph an undirected graph with internal edge weight and
80
* vertex color property maps
81
*
82
* Several overloads of randomWalker() function are provided for
83
* convenience.
84
*
85
* \sa randomWalker(Graph&, EdgeWeightMap, VertexColorMap)
86
* \sa randomWalker(Graph&, EdgeWeightMap, VertexColorMap, Eigen::Matrix <typename boost::property_traits<EdgeWeightMap>::value_type, Eigen::Dynamic, Eigen::Dynamic>&, std::map<typename boost::property_traits <VertexColorMap>::value_type, std::size_t>&)
87
*
88
* \author Sergey Alexandrov
89
* \ingroup segmentation
90
*/
91
92
template
<
class
Graph>
bool
93
randomWalker
(Graph& graph);
94
95
/** \brief Multilabel graph segmentation using random walks.
96
*
97
* This is an overloaded function provided for convenience. See the
98
* documentation for randomWalker().
99
*
100
* \param[in] graph an undirected graph
101
* \param[in] weights an external edge weight property map
102
* \param[in,out] colors an external vertex color property map
103
*
104
* \author Sergey Alexandrov
105
* \ingroup segmentation
106
*/
107
template
<
class
Graph,
class
EdgeWeightMap,
class
VertexColorMap>
bool
108
randomWalker
(Graph& graph,
109
EdgeWeightMap weights,
110
VertexColorMap colors);
111
112
/** \brief Multilabel graph segmentation using random walks.
113
*
114
* This is an overloaded function provided for convenience. See the
115
* documentation for randomWalker().
116
*
117
* \param[in] graph an undirected graph
118
* \param[in] weights an external edge weight property map
119
* \param[in,out] colors an external vertex color property map
120
* \param[out] potentials a matrix with calculated probabilities,
121
* where rows correspond to vertices, and columns
122
* correspond to colors
123
* \param[out] colors_to_columns_map a mapping between colors and
124
* columns in \a potentials matrix
125
*
126
* \author Sergey Alexandrov
127
* \ingroup segmentation
128
*/
129
template
<
class
Graph,
class
EdgeWeightMap,
class
VertexColorMap>
bool
130
randomWalker
(Graph& graph,
131
EdgeWeightMap weights,
132
VertexColorMap colors,
133
Eigen::Matrix<
typename
boost::property_traits<EdgeWeightMap>::value_type, Eigen::Dynamic, Eigen::Dynamic>& potentials,
134
std::map<
typename
boost::property_traits<VertexColorMap>::value_type, std::size_t>& colors_to_columns_map);
135
136
}
137
138
}
139
140
#include <pcl/segmentation/impl/random_walker.hpp>
pcl
This file defines compatibility wrappers for low level I/O functions.
Definition:
convolution.h:45
pcl::segmentation::randomWalker
bool randomWalker(Graph &graph)
Multilabel graph segmentation using random walks.
Definition:
random_walker.hpp:280