Point Cloud Library (PCL)  1.11.1
correspondence_rejection_sample_consensus.h
1 /*
2  * Software License Agreement (BSD License)
3  *
4  * Point Cloud Library (PCL) - www.pointclouds.org
5  * Copyright (c) 2010-2011, Willow Garage, Inc.
6  * Copyright (c) 2012-, Open Perception, Inc.
7  *
8  * All rights reserved.
9  *
10  * Redistribution and use in source and binary forms, with or without
11  * modification, are permitted provided that the following conditions
12  * are met:
13  *
14  * * Redistributions of source code must retain the above copyright
15  * notice, this list of conditions and the following disclaimer.
16  * * Redistributions in binary form must reproduce the above
17  * copyright notice, this list of conditions and the following
18  * disclaimer in the documentation and/or other materials provided
19  * with the distribution.
20  * * Neither the name of the copyright holder(s) nor the names of its
21  * contributors may be used to endorse or promote products derived
22  * from this software without specific prior written permission.
23  *
24  * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
25  * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
26  * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
27  * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
28  * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
29  * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
30  * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
31  * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
32  * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
33  * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
34  * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
35  * POSSIBILITY OF SUCH DAMAGE.
36  *
37  * $Id$
38  *
39  */
40 
41 #pragma once
42 
43 
44 #include <pcl/memory.h>
45 #include <pcl/registration/correspondence_rejection.h>
46 
47 #include <pcl/common/transforms.h>
48 
49 namespace pcl
50 {
51  namespace registration
52  {
53  /** \brief CorrespondenceRejectorSampleConsensus implements a correspondence rejection
54  * using Random Sample Consensus to identify inliers (and reject outliers)
55  * \author Dirk Holz
56  * \ingroup registration
57  */
58  template <typename PointT>
60  {
62  using PointCloudPtr = typename PointCloud::Ptr;
63  using PointCloudConstPtr = typename PointCloud::ConstPtr;
64 
65  public:
69 
70  using Ptr = shared_ptr<CorrespondenceRejectorSampleConsensus<PointT> >;
71  using ConstPtr = shared_ptr<const CorrespondenceRejectorSampleConsensus<PointT> >;
72 
73  /** \brief Empty constructor. Sets the inlier threshold to 5cm (0.05m),
74  * and the maximum number of iterations to 1000.
75  */
77  : inlier_threshold_ (0.05)
78  , max_iterations_ (1000) // std::numeric_limits<int>::max ()
79  , input_ ()
81  , target_ ()
82  , refine_ (false)
83  , save_inliers_ (false)
84  {
85  rejection_name_ = "CorrespondenceRejectorSampleConsensus";
86  }
87 
88  /** \brief Empty destructor. */
90 
91  /** \brief Get a list of valid correspondences after rejection from the original set of correspondences.
92  * \param[in] original_correspondences the set of initial correspondences given
93  * \param[out] remaining_correspondences the resultant filtered set of remaining correspondences
94  */
95  inline void
96  getRemainingCorrespondences (const pcl::Correspondences& original_correspondences,
97  pcl::Correspondences& remaining_correspondences) override;
98 
99  /** \brief Provide a source point cloud dataset (must contain XYZ data!)
100  * \param[in] cloud a cloud containing XYZ data
101  */
102  virtual inline void
103  setInputSource (const PointCloudConstPtr &cloud)
104  {
105  input_ = cloud;
106  }
107 
108  /** \brief Get a pointer to the input point cloud dataset target. */
109  inline PointCloudConstPtr const
110  getInputSource () { return (input_); }
111 
112  /** \brief Provide a target point cloud dataset (must contain XYZ data!)
113  * \param[in] cloud a cloud containing XYZ data
114  */
115  virtual inline void
116  setInputTarget (const PointCloudConstPtr &cloud) { target_ = cloud; }
117 
118  /** \brief Get a pointer to the input point cloud dataset target. */
119  inline PointCloudConstPtr const
120  getInputTarget () { return (target_ ); }
121 
122 
123  /** \brief See if this rejector requires source points */
124  bool
125  requiresSourcePoints () const override
126  { return (true); }
127 
128  /** \brief Blob method for setting the source cloud */
129  void
131  {
132  PointCloudPtr cloud (new PointCloud);
133  fromPCLPointCloud2 (*cloud2, *cloud);
134  setInputSource (cloud);
135  }
136 
137  /** \brief See if this rejector requires a target cloud */
138  bool
139  requiresTargetPoints () const override
140  { return (true); }
141 
142  /** \brief Method for setting the target cloud */
143  void
145  {
146  PointCloudPtr cloud (new PointCloud);
147  fromPCLPointCloud2 (*cloud2, *cloud);
148  setInputTarget (cloud);
149  }
150 
151  /** \brief Set the maximum distance between corresponding points.
152  * Correspondences with distances below the threshold are considered as inliers.
153  * \param[in] threshold Distance threshold in the same dimension as source and target data sets.
154  */
155  inline void
156  setInlierThreshold (double threshold) { inlier_threshold_ = threshold; };
157 
158  /** \brief Get the maximum distance between corresponding points.
159  * \return Distance threshold in the same dimension as source and target data sets.
160  */
161  inline double
163 
164  /** \brief Set the maximum number of iterations.
165  * \param[in] max_iterations Maximum number if iterations to run
166  */
167  inline void
168  setMaximumIterations (int max_iterations) { max_iterations_ = std::max (max_iterations, 0); }
169 
170  /** \brief Get the maximum number of iterations.
171  * \return max_iterations Maximum number if iterations to run
172  */
173  inline int
175 
176  /** \brief Get the best transformation after RANSAC rejection.
177  * \return The homogeneous 4x4 transformation yielding the largest number of inliers.
178  */
179  inline Eigen::Matrix4f
181 
182  /** \brief Specify whether the model should be refined internally using the variance of the inliers
183  * \param[in] refine true if the model should be refined, false otherwise
184  */
185  inline void
186  setRefineModel (const bool refine)
187  {
188  refine_ = refine;
189  }
190 
191  /** \brief Get the internal refine parameter value as set by the user using setRefineModel */
192  inline bool
193  getRefineModel () const
194  {
195  return (refine_);
196  }
197 
198  /** \brief Get the inlier indices found by the correspondence rejector. This information is only saved if setSaveInliers(true) was called in advance.
199  * \param[out] inlier_indices Indices for the inliers
200  */
201  inline void
202  getInliersIndices (std::vector<int> &inlier_indices) { inlier_indices = inlier_indices_; }
203 
204  /** \brief Set whether to save inliers or not
205  * \param[in] s True to save inliers / False otherwise
206  */
207  inline void
208  setSaveInliers (bool s) { save_inliers_ = s; }
209 
210  /** \brief Get whether the rejector is configured to save inliers */
211  inline bool
213 
214 
215  protected:
216 
217  /** \brief Apply the rejection algorithm.
218  * \param[out] correspondences the set of resultant correspondences.
219  */
220  inline void
221  applyRejection (pcl::Correspondences &correspondences) override
222  {
224  }
225 
227 
229 
230  PointCloudConstPtr input_;
231  PointCloudPtr input_transformed_;
232  PointCloudConstPtr target_;
233 
234  Eigen::Matrix4f best_transformation_;
235 
236  bool refine_;
237  std::vector<int> inlier_indices_;
239 
240  public:
242  };
243  }
244 }
245 
246 #include <pcl/registration/impl/correspondence_rejection_sample_consensus.hpp>
void fromPCLPointCloud2(const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud, const MsgFieldMap &field_map)
Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map...
Definition: conversions.h:168
shared_ptr< const CorrespondenceRejector > ConstPtr
double getInlierThreshold()
Get the maximum distance between corresponding points.
shared_ptr< PointCloud< PointT > > Ptr
Definition: point_cloud.h:429
Defines functions, macros and traits for allocating and using memory.
shared_ptr< CorrespondenceRejector > Ptr
CorrespondenceRejector represents the base class for correspondence rejection methods ...
shared_ptr< const ::pcl::PCLPointCloud2 > ConstPtr
void setTargetPoints(pcl::PCLPointCloud2::ConstPtr cloud2) override
Method for setting the target cloud.
void getInliersIndices(std::vector< int > &inlier_indices)
Get the inlier indices found by the correspondence rejector.
bool requiresTargetPoints() const override
See if this rejector requires a target cloud.
#define PCL_MAKE_ALIGNED_OPERATOR_NEW
Macro to signal a class requires a custom allocator.
Definition: memory.h:63
const std::string & getClassName() const
Get a string representation of the name of this class.
Eigen::Matrix4f getBestTransformation()
Get the best transformation after RANSAC rejection.
void applyRejection(pcl::Correspondences &correspondences) override
Apply the rejection algorithm.
virtual void setInputTarget(const PointCloudConstPtr &cloud)
Provide a target point cloud dataset (must contain XYZ data!)
void setMaximumIterations(int max_iterations)
Set the maximum number of iterations.
PointCloudConstPtr const getInputSource()
Get a pointer to the input point cloud dataset target.
bool requiresSourcePoints() const override
See if this rejector requires source points.
void setInlierThreshold(double threshold)
Set the maximum distance between corresponding points.
bool getRefineModel() const
Get the internal refine parameter value as set by the user using setRefineModel.
PointCloud represents the base class in PCL for storing collections of 3D points. ...
Definition: distances.h:55
CorrespondenceRejectorSampleConsensus implements a correspondence rejection using Random Sample Conse...
PointCloudConstPtr const getInputTarget()
Get a pointer to the input point cloud dataset target.
CorrespondencesConstPtr input_correspondences_
The input correspondences.
shared_ptr< const PointCloud< PointT > > ConstPtr
Definition: point_cloud.h:430
virtual void setInputSource(const PointCloudConstPtr &cloud)
Provide a source point cloud dataset (must contain XYZ data!)
std::string rejection_name_
The name of the rejection method.
std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > > Correspondences
bool getSaveInliers()
Get whether the rejector is configured to save inliers.
void getRemainingCorrespondences(const pcl::Correspondences &original_correspondences, pcl::Correspondences &remaining_correspondences) override
Get a list of valid correspondences after rejection from the original set of correspondences.
void setRefineModel(const bool refine)
Specify whether the model should be refined internally using the variance of the inliers.
void setSourcePoints(pcl::PCLPointCloud2::ConstPtr cloud2) override
Blob method for setting the source cloud.