141 lines
5.9 KiB
C++
141 lines
5.9 KiB
C++
/*
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* Software License Agreement (BSD License)
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*
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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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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above
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* copyright notice, this list of conditions and the following
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* disclaimer in the documentation and/or other materials provided
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* with the distribution.
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* * Neither the name of Willow Garage, Inc. nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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*/
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#pragma once
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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/Core> // for Matrix
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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, std::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, std::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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