206 lines
7.9 KiB
C++
206 lines
7.9 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) 2010-2011, Willow Garage, 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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// PCL includes
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#include <pcl/pcl_base.h>
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#include <pcl/search/search.h> // for Search
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#include <pcl/pcl_config.h>
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#include <functional>
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namespace pcl
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{
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/** \brief @b Keypoint represents the base class for key points.
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* \author Bastian Steder
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* \ingroup keypoints
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*/
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template <typename PointInT, typename PointOutT>
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class Keypoint : public PCLBase<PointInT>
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{
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public:
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using Ptr = shared_ptr<Keypoint<PointInT, PointOutT> >;
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using ConstPtr = shared_ptr<const Keypoint<PointInT, PointOutT> >;
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using PCLBase<PointInT>::indices_;
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using PCLBase<PointInT>::input_;
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using BaseClass = PCLBase<PointInT>;
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using KdTree = pcl::search::Search<PointInT>;
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using KdTreePtr = typename KdTree::Ptr;
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using PointCloudIn = pcl::PointCloud<PointInT>;
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using PointCloudInPtr = typename PointCloudIn::Ptr;
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using PointCloudInConstPtr = typename PointCloudIn::ConstPtr;
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using PointCloudOut = pcl::PointCloud<PointOutT>;
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using SearchMethod = std::function<int (pcl::index_t, double, pcl::Indices &, std::vector<float> &)>;
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using SearchMethodSurface = std::function<int (const PointCloudIn &cloud, pcl::index_t index, double, pcl::Indices &, std::vector<float> &)>;
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public:
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/** \brief Empty constructor. */
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Keypoint () :
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BaseClass (),
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search_method_surface_ (),
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surface_ (),
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tree_ (),
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search_parameter_ (0),
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search_radius_ (0),
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k_ (0)
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{};
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/** \brief Empty destructor */
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~Keypoint () {}
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/** \brief Provide a pointer to the input dataset that we need to estimate features at every point for.
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* \param cloud the const boost shared pointer to a PointCloud message
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*/
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virtual void
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setSearchSurface (const PointCloudInConstPtr &cloud) { surface_ = cloud; }
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/** \brief Get a pointer to the surface point cloud dataset. */
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inline PointCloudInConstPtr
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getSearchSurface () { return (surface_); }
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/** \brief Provide a pointer to the search object.
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* \param tree a pointer to the spatial search object.
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*/
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inline void
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setSearchMethod (const KdTreePtr &tree) { tree_ = tree; }
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/** \brief Get a pointer to the search method used. */
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inline KdTreePtr
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getSearchMethod () { return (tree_); }
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/** \brief Get the internal search parameter. */
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inline double
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getSearchParameter () { return (search_parameter_); }
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/** \brief Set the number of k nearest neighbors to use for the feature estimation.
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* \param k the number of k-nearest neighbors
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*/
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inline void
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setKSearch (int k) { k_ = k; }
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/** \brief get the number of k nearest neighbors used for the feature estimation. */
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inline int
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getKSearch () { return (k_); }
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/** \brief Set the sphere radius that is to be used for determining the nearest neighbors used for the
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* key point detection
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* \param radius the sphere radius used as the maximum distance to consider a point a neighbor
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*/
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inline void
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setRadiusSearch (double radius) { search_radius_ = radius; }
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/** \brief Get the sphere radius used for determining the neighbors. */
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inline double
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getRadiusSearch () { return (search_radius_); }
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/** \brief \return the keypoints indices in the input cloud.
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* \note not all the daughter classes populate the keypoints indices so check emptiness before use.
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*/
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pcl::PointIndicesConstPtr
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getKeypointsIndices () { return (keypoints_indices_); }
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/** \brief Base method for key point detection for all points given in <setInputCloud (), setIndices ()> using
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* the surface in setSearchSurface () and the spatial locator in setSearchMethod ()
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* \param output the resultant point cloud model dataset containing the estimated features
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*/
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inline void
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compute (PointCloudOut &output);
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/** \brief Search for k-nearest neighbors using the spatial locator from \a setSearchmethod, and the given surface
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* from \a setSearchSurface.
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* \param index the index of the query point
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* \param parameter the search parameter (either k or radius)
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* \param indices the resultant vector of indices representing the k-nearest neighbors
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* \param distances the resultant vector of distances representing the distances from the query point to the
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* k-nearest neighbors
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*/
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inline int
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searchForNeighbors (pcl::index_t index, double parameter, pcl::Indices &indices, std::vector<float> &distances) const
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{
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if (surface_ == input_) // if the two surfaces are the same
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return (search_method_ (index, parameter, indices, distances));
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return (search_method_surface_ (*input_, index, parameter, indices, distances));
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}
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protected:
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using PCLBase<PointInT>::deinitCompute;
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virtual bool
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initCompute ();
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/** \brief The key point detection method's name. */
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std::string name_;
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/** \brief The search method template for indices. */
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SearchMethod search_method_;
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/** \brief The search method template for points. */
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SearchMethodSurface search_method_surface_;
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/** \brief An input point cloud describing the surface that is to be used for nearest neighbors estimation. */
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PointCloudInConstPtr surface_;
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/** \brief A pointer to the spatial search object. */
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KdTreePtr tree_;
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/** \brief The actual search parameter (casted from either \a search_radius_ or \a k_). */
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double search_parameter_;
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/** \brief The nearest neighbors search radius for each point. */
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double search_radius_;
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/** \brief The number of K nearest neighbors to use for each point. */
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int k_;
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/** \brief Indices of the keypoints in the input cloud. */
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pcl::PointIndicesPtr keypoints_indices_;
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/** \brief Get a string representation of the name of this class. */
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inline const std::string&
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getClassName () const { return (name_); }
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/** \brief Abstract key point detection method. */
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virtual void
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detectKeypoints (PointCloudOut &output) = 0;
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};
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}
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#include <pcl/keypoints/impl/keypoint.hpp>
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