hv_papazov.h
/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2010-2011, Willow Garage, Inc.
*
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
* * Neither the name of Willow Garage, Inc. nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*/
#pragma once
#include <pcl/pcl_macros.h>
#include <pcl/recognition/hv/hypotheses_verification.h>
#include <boost/graph/adjacency_list.hpp>
#include <memory>
namespace pcl
{
/** \brief A hypothesis verification method proposed in
* "An Efficient RANSAC for 3D Object Recognition in Noisy and Occluded Scenes", C. Papazov and D. Burschka, ACCV 2010
* \author Aitor Aldoma, Federico Tombari
*/
template<typename ModelT, typename SceneT>
class PCL_EXPORTS PapazovHV : public HypothesisVerification<ModelT, SceneT>
{
using HypothesisVerification<ModelT, SceneT>::mask_;
using HypothesisVerification<ModelT, SceneT>::scene_cloud_downsampled_;
using HypothesisVerification<ModelT, SceneT>::scene_downsampled_tree_;
using HypothesisVerification<ModelT, SceneT>::visible_models_;
using HypothesisVerification<ModelT, SceneT>::complete_models_;
using HypothesisVerification<ModelT, SceneT>::resolution_;
using HypothesisVerification<ModelT, SceneT>::inliers_threshold_;
float conflict_threshold_size_;
float penalty_threshold_;
float support_threshold_;
class RecognitionModel
{
public:
std::vector<int> explained_; //indices vector referencing explained_by_RM_
typename pcl::PointCloud<ModelT>::Ptr cloud_;
typename pcl::PointCloud<ModelT>::Ptr complete_cloud_;
int bad_information_;
int id_;
};
using RecognitionModelPtr = std::shared_ptr<RecognitionModel>;
std::vector<int> explained_by_RM_; //represents the points of scene_cloud_ that are explained by the recognition models
std::vector<RecognitionModelPtr> recognition_models_;
std::vector<std::vector<RecognitionModelPtr>> points_explained_by_rm_; //if inner size > 1, conflict
std::map<int, RecognitionModelPtr> graph_id_model_map_;
using Graph = boost::adjacency_list<boost::vecS, boost::vecS, boost::undirectedS, RecognitionModelPtr>;
Graph conflict_graph_;
//builds the conflict_graph
void buildConflictGraph();
//non-maxima suppresion on the conflict graph
void nonMaximaSuppresion();
//create recognition models
void initialize();
public:
PapazovHV() : HypothesisVerification<ModelT,SceneT>() {
support_threshold_ = 0.1f;
penalty_threshold_ = 0.1f;
conflict_threshold_size_ = 0.02f;
}
void setConflictThreshold(float t) {
conflict_threshold_size_ = t;
}
void setSupportThreshold(float t) {
support_threshold_ = t;
}
void setPenaltyThreshold(float t) {
penalty_threshold_ = t;
}
//build conflict graph
//non-maxima supression
void verify() override;
};
}
#ifdef PCL_NO_PRECOMPILE
#include <pcl/recognition/impl/hv/hv_papazov.hpp>
#endif
pcl::HypothesisVerification
Abstract class for hypotheses verification methods.
Definition: hypotheses_verification.h:55
pcl::PapazovHV
A hypothesis verification method proposed in "An Efficient RANSAC for 3D Object Recognition in Noisy ...
Definition: hv_papazov.h:55
pcl::PapazovHV::setConflictThreshold
void setConflictThreshold(float t)
Definition: hv_papazov.h:102
pcl::PapazovHV::setSupportThreshold
void setSupportThreshold(float t)
Definition: hv_papazov.h:106
pcl::PapazovHV::setPenaltyThreshold
void setPenaltyThreshold(float t)
Definition: hv_papazov.h:110
pcl::PapazovHV::PapazovHV
PapazovHV()
Definition: hv_papazov.h:96
pcl::PointCloud::Ptr
shared_ptr< PointCloud< PointT > > Ptr
Definition: point_cloud.h:413
pcl
Definition: convolution.h:46
pcl_macros.h
Defines all the PCL and non-PCL macros used.
PCL_EXPORTS
#define PCL_EXPORTS
Definition: pcl_macros.h:323