Point Cloud Library (PCL)
1.9.1
segmentation
include
pcl
segmentation
random_walker.h
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/*
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* Software License Agreement (BSD License)
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* Point Cloud Library (PCL) - www.pointclouds.org
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* Copyright (c) 2012-, Open Perception, Inc.
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*
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* All rights reserved.
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#ifndef PCL_SEGMENTATION_RANDOM_WALKER_H
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#define PCL_SEGMENTATION_RANDOM_WALKER_H
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#include <boost/graph/adjacency_list.hpp>
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#include <boost/graph/graph_concepts.hpp>
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#include <boost/concept/assert.hpp>
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#include <Eigen/Dense>
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namespace
pcl
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{
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namespace
segmentation
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{
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/** \brief Multilabel graph segmentation using random walks.
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*
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* This is an implementation of the algorithm described in "Random Walks
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* for Image Segmentation" by Leo Grady.
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*
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* Given a weighted undirected graph and a small number of user-defined
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* labels this algorithm analytically determines the probability that a
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* random walker starting at each unlabeled vertex will first reach one
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* of the prelabeled vertices. The unlabeled vertices are then assigned
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* to the label for which the greatest probability is calculated.
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*
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* The input is a BGL graph, a property map that associates a weight to
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* each edge of the graph, and a property map that contains initial
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* vertex colors (the term "color" is used interchangeably with "label").
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*
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* \note The colors of unlabeled vertices should be set to 0, the colors
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* of labeled vetices could be any positive numbers.
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*
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* \note This is the responsibility of the user to make sure that every
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* connected component of the graph has at least one colored vertex. If
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* the user failed to do so, then the behavior of the algorithm is
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* undefined, i.e. it may or may not succeed, and also may or may not
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* report failure.
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*
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* The output of the algorithm (i.e. label assignment) is written back
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* to the color map.
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*
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* \param[in] graph an undirected graph with internal edge weight and
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* vertex color property maps
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*
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* Several overloads of randomWalker() function are provided for
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* convenience.
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*
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* \sa randomWalker(Graph&, EdgeWeightMap, VertexColorMap)
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* \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, size_t>&)
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*
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* \author Sergey Alexandrov
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* \ingroup segmentation
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*/
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template
<
class
Graph>
bool
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randomWalker
(Graph& graph);
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/** \brief Multilabel graph segmentation using random walks.
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*
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* This is an overloaded function provided for convenience. See the
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* documentation for randomWalker().
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*
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* \param[in] graph an undirected graph
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* \param[in] weights an external edge weight property map
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* \param[in,out] colors an external vertex color property map
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*
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* \author Sergey Alexandrov
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* \ingroup segmentation
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*/
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template
<
class
Graph,
class
EdgeWeightMap,
class
VertexColorMap>
bool
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randomWalker
(Graph& graph,
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EdgeWeightMap weights,
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VertexColorMap colors);
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/** \brief Multilabel graph segmentation using random walks.
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*
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* This is an overloaded function provided for convenience. See the
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* documentation for randomWalker().
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*
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* \param[in] graph an undirected graph
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* \param[in] weights an external edge weight property map
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* \param[in,out] colors an external vertex color property map
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* \param[out] potentials a matrix with calculated probabilities,
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* where rows correspond to vertices, and columns
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* correspond to colors
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* \param[out] colors_to_columns_map a mapping between colors and
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* columns in \a potentials matrix
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*
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* \author Sergey Alexandrov
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* \ingroup segmentation
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*/
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template
<
class
Graph,
class
EdgeWeightMap,
class
VertexColorMap>
bool
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randomWalker
(Graph& graph,
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EdgeWeightMap weights,
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VertexColorMap colors,
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Eigen::Matrix<
typename
boost::property_traits<EdgeWeightMap>::value_type, Eigen::Dynamic, Eigen::Dynamic>& potentials,
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std::map<
typename
boost::property_traits<VertexColorMap>::value_type,
size_t
>& colors_to_columns_map);
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}
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}
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#include <pcl/segmentation/impl/random_walker.hpp>
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#endif
/* PCL_SEGMENTATION_RANDOM_WALKER_H */
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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:283