177 lines
7.3 KiB
C
177 lines
7.3 KiB
C
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/*
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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) 2010-2011, Willow Garage, Inc.
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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 the copyright holder(s) 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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* $Id$
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*/
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#pragma once
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#include <pcl/search/search.h>
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#include <pcl/kdtree/kdtree_flann.h>
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namespace pcl
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{
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// Forward declarations
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template <typename T> class PointRepresentation;
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namespace search
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{
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/** \brief @b search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search
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* functions using KdTree structure. KdTree is a generic type of 3D spatial locator using kD-tree structures.
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* The class is making use of the FLANN (Fast Library for Approximate Nearest Neighbor) project
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* by Marius Muja and David Lowe.
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*
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* \author Radu B. Rusu
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* \ingroup search
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*/
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template<typename PointT, class Tree = pcl::KdTreeFLANN<PointT> >
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class KdTree: public Search<PointT>
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{
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public:
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using PointCloud = typename Search<PointT>::PointCloud;
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using PointCloudConstPtr = typename Search<PointT>::PointCloudConstPtr;
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using pcl::search::Search<PointT>::indices_;
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using pcl::search::Search<PointT>::input_;
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using pcl::search::Search<PointT>::getIndices;
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using pcl::search::Search<PointT>::getInputCloud;
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using pcl::search::Search<PointT>::nearestKSearch;
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using pcl::search::Search<PointT>::radiusSearch;
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using pcl::search::Search<PointT>::sorted_results_;
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using Ptr = shared_ptr<KdTree<PointT, Tree> >;
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using ConstPtr = shared_ptr<const KdTree<PointT, Tree> >;
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using KdTreePtr = typename Tree::Ptr;
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using KdTreeConstPtr = typename Tree::ConstPtr;
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using PointRepresentationConstPtr = typename PointRepresentation<PointT>::ConstPtr;
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/** \brief Constructor for KdTree.
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*
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* \param[in] sorted set to true if the nearest neighbor search results
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* need to be sorted in ascending order based on their distance to the
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* query point
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*
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*/
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KdTree (bool sorted = true);
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/** \brief Destructor for KdTree. */
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~KdTree ()
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{
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}
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/** \brief Provide a pointer to the point representation to use to convert points into k-D vectors.
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* \param[in] point_representation the const boost shared pointer to a PointRepresentation
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*/
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void
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setPointRepresentation (const PointRepresentationConstPtr &point_representation);
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/** \brief Get a pointer to the point representation used when converting points into k-D vectors. */
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inline PointRepresentationConstPtr
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getPointRepresentation () const
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{
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return (tree_->getPointRepresentation ());
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}
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/** \brief Sets whether the results have to be sorted or not.
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* \param[in] sorted_results set to true if the radius search results should be sorted
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*/
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void
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setSortedResults (bool sorted_results) override;
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/** \brief Set the search epsilon precision (error bound) for nearest neighbors searches.
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* \param[in] eps precision (error bound) for nearest neighbors searches
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*/
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void
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setEpsilon (float eps);
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/** \brief Get the search epsilon precision (error bound) for nearest neighbors searches. */
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inline float
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getEpsilon () const
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{
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return (tree_->getEpsilon ());
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}
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/** \brief Provide a pointer to the input dataset.
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* \param[in] cloud the const boost shared pointer to a PointCloud message
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* \param[in] indices the point indices subset that is to be used from \a cloud
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*/
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void
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setInputCloud (const PointCloudConstPtr& cloud,
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const IndicesConstPtr& indices = IndicesConstPtr ()) override;
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/** \brief Search for the k-nearest neighbors for the given query point.
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* \param[in] point the given query point
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* \param[in] k the number of neighbors to search for
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* \param[out] k_indices the resultant indices of the neighboring points (must be resized to \a k a priori!)
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* \param[out] k_sqr_distances the resultant squared distances to the neighboring points (must be resized to \a k
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* a priori!)
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* \return number of neighbors found
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*/
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int
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nearestKSearch (const PointT &point, int k,
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Indices &k_indices,
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std::vector<float> &k_sqr_distances) const override;
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/** \brief Search for all the nearest neighbors of the query point in a given radius.
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* \param[in] point the given query point
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* \param[in] radius the radius of the sphere bounding all of p_q's neighbors
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* \param[out] k_indices the resultant indices of the neighboring points
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* \param[out] k_sqr_distances the resultant squared distances to the neighboring points
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* \param[in] max_nn if given, bounds the maximum returned neighbors to this value. If \a max_nn is set to
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* 0 or to a number higher than the number of points in the input cloud, all neighbors in \a radius will be
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* returned.
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* \return number of neighbors found in radius
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*/
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int
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radiusSearch (const PointT& point, double radius,
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Indices &k_indices,
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std::vector<float> &k_sqr_distances,
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unsigned int max_nn = 0) const override;
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protected:
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/** \brief A pointer to the internal KdTree object. */
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KdTreePtr tree_;
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};
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}
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}
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#ifdef PCL_NO_PRECOMPILE
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#include <pcl/search/impl/kdtree.hpp>
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#else
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#define PCL_INSTANTIATE_KdTree(T) template class PCL_EXPORTS pcl::search::KdTree<T>;
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#endif
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