Point Cloud Library (PCL)  1.12.1-dev
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39
40 #pragma once
41
42 #include <pcl/filters/filter_indices.h>
43 #include <pcl/search/search.h> // for Search, Search<>::Ptr
44
45 namespace pcl
46 {
47  /** \brief @b RadiusOutlierRemoval filters points in a cloud based on the number of neighbors they have.
48  * \details Iterates through the entire input once, and for each point, retrieves the number of neighbors within a certain radius.
49  * The point will be considered an outlier if it has too few neighbors, as determined by setMinNeighborsInRadius().
51  * <br>
52  * The neighbors found for each query point will be found amongst ALL points of setInputCloud(), not just those indexed by setIndices().
53  * The setIndices() method only indexes the points that will be iterated through as search query points.
54  * <br><br>
55  * Usage example:
56  * \code
57  * pcl::RadiusOutlierRemoval<PointType> rorfilter (true); // Initializing with true will allow us to extract the removed indices
58  * rorfilter.setInputCloud (cloud_in);
61  * rorfilter.setNegative (true);
62  * rorfilter.filter (*cloud_out);
63  * // The resulting cloud_out contains all points of cloud_in that have 4 or less neighbors within the 0.1 search radius
64  * indices_rem = rorfilter.getRemovedIndices ();
65  * // The indices_rem array indexes all points of cloud_in that have 5 or more neighbors within the 0.1 search radius
66  * \endcode
67  * \author Radu Bogdan Rusu
68  * \ingroup filters
69  */
70  template<typename PointT>
71  class RadiusOutlierRemoval : public FilterIndices<PointT>
72  {
73  protected:
75  using PointCloudPtr = typename PointCloud::Ptr;
78
79  public:
80
81  using Ptr = shared_ptr<RadiusOutlierRemoval<PointT> >;
82  using ConstPtr = shared_ptr<const RadiusOutlierRemoval<PointT> >;
83
84
85  /** \brief Constructor.
86  * \param[in] extract_removed_indices Set to true if you want to be able to extract the indices of points being removed (default = false).
87  */
88  RadiusOutlierRemoval (bool extract_removed_indices = false) :
89  FilterIndices<PointT> (extract_removed_indices),
90  searcher_ (),
93  {
95  }
96
97  /** \brief Set the radius of the sphere that will determine which points are neighbors.
98  * \details The number of points within this distance from the query point will need to be equal or greater
99  * than setMinNeighborsInRadius() in order to be classified as an inlier point (i.e. will not be filtered).
100  * \param[in] radius The radius of the sphere for nearest neighbor searching.
101  */
102  inline void
104  {
106  }
107
108  /** \brief Get the radius of the sphere that will determine which points are neighbors.
109  * \details The number of points within this distance from the query point will need to be equal or greater
110  * than setMinNeighborsInRadius() in order to be classified as an inlier point (i.e. will not be filtered).
111  * \return The radius of the sphere for nearest neighbor searching.
112  */
113  inline double
115  {
117  }
118
119  /** \brief Set the number of neighbors that need to be present in order to be classified as an inlier.
120  * \details The number of points within setRadiusSearch() from the query point will need to be equal or greater
121  * than this number in order to be classified as an inlier point (i.e. will not be filtered).
122  * \param min_pts The minimum number of neighbors (default = 1).
123  */
124  inline void
126  {
128  }
129
130  /** \brief Get the number of neighbors that need to be present in order to be classified as an inlier.
131  * \details The number of points within setRadiusSearch() from the query point will need to be equal or greater
132  * than this number in order to be classified as an inlier point (i.e. will not be filtered).
133  * \return The minimum number of neighbors (default = 1).
134  */
135  inline int
137  {
139  }
140
141  protected:
151
152  /** \brief Filtered results are indexed by an indices array.
153  * \param[out] indices The resultant indices.
154  */
155  void
156  applyFilter (Indices &indices) override
157  {
158  applyFilterIndices (indices);
159  }
160
161  /** \brief Filtered results are indexed by an indices array.
162  * \param[out] indices The resultant indices.
163  */
164  void
165  applyFilterIndices (Indices &indices);
166
167  private:
168  /** \brief A pointer to the spatial search object. */
169  SearcherPtr searcher_;
170
171  /** \brief The nearest neighbors search radius for each point. */
173
174  /** \brief The minimum number of neighbors that a point needs to have in the given search radius to be considered an inlier. */
176  };
177
178  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
179  /** \brief @b RadiusOutlierRemoval is a simple filter that removes outliers if the number of neighbors in a certain
180  * search radius is smaller than a given K.
181  * \author Radu Bogdan Rusu
182  * \ingroup filters
183  */
184  template<>
185  class PCL_EXPORTS RadiusOutlierRemoval<pcl::PCLPointCloud2> : public FilterIndices<pcl::PCLPointCloud2>
186  {
189
192
194  using KdTreePtr = pcl::search::Search<pcl::PointXYZ>::Ptr;
195
199
200  public:
201  /** \brief Empty constructor. */
202  RadiusOutlierRemoval (bool extract_removed_indices = false) :
203  FilterIndices<pcl::PCLPointCloud2>::FilterIndices (extract_removed_indices),
205  {
207  }
208
209  /** \brief Set the sphere radius that is to be used for determining the k-nearest neighbors for filtering.
210  * \param radius the sphere radius that is to contain all k-nearest neighbors
211  */
212  inline void
214  {
216  }
217
218  /** \brief Get the sphere radius used for determining the k-nearest neighbors. */
219  inline double
221  {
223  }
224
225  /** \brief Set the minimum number of neighbors that a point needs to have in the given search radius in order to
226  * be considered an inlier (i.e., valid).
227  * \param min_pts the minimum number of neighbors
228  */
229  inline void
231  {
233  }
234
235  /** \brief Get the minimum number of neighbors that a point needs to have in the given search radius to be
236  * considered an inlier and avoid being filtered.
237  */
238  inline double
240  {
242  }
243
244  protected:
245  /** \brief The nearest neighbors search radius for each point. */
247
248  /** \brief The minimum number of neighbors that a point needs to have in the given search radius to be considered
249  * an inlier.
250  */
252
253  /** \brief A pointer to the spatial search object. */
254  KdTreePtr searcher_;
255
256  void
257  applyFilter (PCLPointCloud2 &output) override;
258
259  void
260  applyFilter (Indices &indices) override;
261  };
262 }
263
264 #ifdef PCL_NO_PRECOMPILE
266 #endif
Filter represents the base filter class.
Definition: filter.h:81
shared_ptr< Filter< PointT > > Ptr
Definition: filter.h:83
shared_ptr< const Filter< PointT > > ConstPtr
Definition: filter.h:84
std::string filter_name_
The filter name.
Definition: filter.h:158
FilterIndices represents the base class for filters that are about binary point removal.
PCLPointCloud2::Ptr PCLPointCloud2Ptr
Definition: pcl_base.h:185
PCLPointCloud2::ConstPtr PCLPointCloud2ConstPtr
Definition: pcl_base.h:186
PCL base class.
Definition: pcl_base.h:70
typename PointCloud::Ptr PointCloudPtr
Definition: pcl_base.h:73
typename PointCloud::ConstPtr PointCloudConstPtr
Definition: pcl_base.h:74
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition: point_cloud.h:173
shared_ptr< PointCloud< PointT > > Ptr
Definition: point_cloud.h:413
shared_ptr< const PointCloud< PointT > > ConstPtr
Definition: point_cloud.h:414
void applyFilter(Indices &indices) override
Abstract filter method for point cloud indices.
Get the sphere radius used for determining the k-nearest neighbors.
Get the minimum number of neighbors that a point needs to have in the given search radius to be consi...
Set the sphere radius that is to be used for determining the k-nearest neighbors for filtering.
KdTreePtr searcher_
A pointer to the spatial search object.
The nearest neighbors search radius for each point.
The minimum number of neighbors that a point needs to have in the given search radius to be considere...
Empty constructor.
void applyFilter(PCLPointCloud2 &output) override
Abstract filter method for point cloud.
Set the minimum number of neighbors that a point needs to have in the given search radius in order to...
RadiusOutlierRemoval filters points in a cloud based on the number of neighbors they have.
void applyFilterIndices(Indices &indices)
Filtered results are indexed by an indices array.
Get the number of neighbors that need to be present in order to be classified as an inlier.
void applyFilter(Indices &indices) override
Filtered results are indexed by an indices array.
Set the number of neighbors that need to be present in order to be classified as an inlier.
Set the radius of the sphere that will determine which points are neighbors.
Constructor.
typename pcl::search::Search< PointT >::Ptr SearcherPtr