155 lines
5.9 KiB
C++
155 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) 2010-2012, 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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* $Id$
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*
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*/
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#pragma once
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#include <pcl/recognition/cg/correspondence_grouping.h>
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#include <pcl/point_cloud.h>
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namespace pcl
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{
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/** \brief Class implementing a 3D correspondence grouping enforcing geometric consistency among feature correspondences
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*
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* \author Federico Tombari, Tommaso Cavallari, Aitor Aldoma
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* \ingroup recognition
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*/
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template<typename PointModelT, typename PointSceneT>
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class GeometricConsistencyGrouping : public CorrespondenceGrouping<PointModelT, PointSceneT>
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{
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public:
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using PointCloud = pcl::PointCloud<PointModelT>;
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using PointCloudPtr = typename PointCloud::Ptr;
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using PointCloudConstPtr = typename PointCloud::ConstPtr;
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using SceneCloudConstPtr = typename pcl::CorrespondenceGrouping<PointModelT, PointSceneT>::SceneCloudConstPtr;
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/** \brief Constructor */
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GeometricConsistencyGrouping ()
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: gc_threshold_ (3)
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, gc_size_ (1.0)
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{}
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/** \brief Sets the minimum cluster size
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* \param[in] threshold the minimum cluster size
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*/
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inline void
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setGCThreshold (int threshold)
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{
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gc_threshold_ = threshold;
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}
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/** \brief Gets the minimum cluster size.
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*
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* \return the minimum cluster size used by GC.
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*/
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inline int
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getGCThreshold () const
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{
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return (gc_threshold_);
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}
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/** \brief Sets the consensus set resolution. This should be in metric units.
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*
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* \param[in] gc_size consensus set resolution.
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*/
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inline void
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setGCSize (double gc_size)
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{
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gc_size_ = gc_size;
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}
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/** \brief Gets the consensus set resolution.
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*
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* \return the consensus set resolution.
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*/
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inline double
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getGCSize () const
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{
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return (gc_size_);
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}
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/** \brief The main function, recognizes instances of the model into the scene set by the user.
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*
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* \param[out] transformations a vector containing one transformation matrix for each instance of the model recognized into the scene.
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*
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* \return true if the recognition had been successful or false if errors have occurred.
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*/
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bool
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recognize (std::vector<Eigen::Matrix4f, Eigen::aligned_allocator<Eigen::Matrix4f> > &transformations);
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/** \brief The main function, recognizes instances of the model into the scene set by the user.
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*
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* \param[out] transformations a vector containing one transformation matrix for each instance of the model recognized into the scene.
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* \param[out] clustered_corrs a vector containing the correspondences for each instance of the model found within the input data (the same output of clusterCorrespondences).
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*
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* \return true if the recognition had been successful or false if errors have occurred.
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*/
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bool
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recognize (std::vector<Eigen::Matrix4f, Eigen::aligned_allocator<Eigen::Matrix4f> > &transformations, std::vector<pcl::Correspondences> &clustered_corrs);
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protected:
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using CorrespondenceGrouping<PointModelT, PointSceneT>::input_;
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using CorrespondenceGrouping<PointModelT, PointSceneT>::scene_;
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using CorrespondenceGrouping<PointModelT, PointSceneT>::model_scene_corrs_;
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/** \brief Minimum cluster size. It shouldn't be less than 3, since at least 3 correspondences are needed to compute the 6DOF pose */
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int gc_threshold_;
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/** \brief Resolution of the consensus set used to cluster correspondences together*/
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double gc_size_;
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/** \brief Transformations found by clusterCorrespondences method. */
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std::vector<Eigen::Matrix4f, Eigen::aligned_allocator<Eigen::Matrix4f> > found_transformations_;
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/** \brief Cluster the input correspondences in order to distinguish between different instances of the model into the scene.
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*
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* \param[out] model_instances a vector containing the clustered correspondences for each model found on the scene.
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* \return true if the clustering had been successful or false if errors have occurred.
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*/
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void
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clusterCorrespondences (std::vector<Correspondences> &model_instances) override;
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};
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}
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#ifdef PCL_NO_PRECOMPILE
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#include <pcl/recognition/impl/cg/geometric_consistency.hpp>
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#endif
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