Point Cloud Library (PCL) 1.12.1
octree.h
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38
39#pragma once
40
41#include <pcl/search/search.h>
42#include <pcl/octree/octree_search.h>
43
44namespace pcl
45{
46 namespace search
47 {
48 /** \brief @b search::Octree is a wrapper class which implements nearest neighbor search operations based on the
49 * pcl::octree::Octree structure.
50 *
51 * The octree pointcloud class needs to be initialized with its voxel
52 * resolution. Its bounding box is automatically adjusted according to the
53 * pointcloud dimension or it can be predefined. Note: The tree depth
54 * equates to the resolution and the bounding box dimensions of the
55 * octree.
56 *
57 * \note typename: PointT: type of point used in pointcloud
58 * \note typename: LeafT: leaf node class (usuallt templated with integer indices values)
59 * \note typename: OctreeT: octree implementation ()
60 *
61 * \author Julius Kammerl
62 * \ingroup search
63 */
64 template<typename PointT,
66 typename BranchTWrap = pcl::octree::OctreeContainerEmpty,
68 class Octree: public Search<PointT>
69 {
70 public:
71 // public typedefs
72 using Ptr = shared_ptr<pcl::search::Octree<PointT,LeafTWrap,BranchTWrap,OctreeT> >;
73 using ConstPtr = shared_ptr<const pcl::search::Octree<PointT,LeafTWrap,BranchTWrap,OctreeT> >;
74
78
79 // Boost shared pointers
83
87
88 /** \brief Octree constructor.
89 * \param[in] resolution octree resolution at lowest octree level
90 */
91 Octree (const double resolution)
92 : Search<PointT> ("Octree")
93 , tree_ (new pcl::octree::OctreePointCloudSearch<PointT, LeafTWrap, BranchTWrap> (resolution))
94 {
95 }
96
97 /** \brief Empty Destructor. */
98
100 {
101 }
102
103 /** \brief Provide a pointer to the input dataset.
104 * \param[in] cloud the const boost shared pointer to a PointCloud message
105 */
106 inline void
108 {
109 tree_->deleteTree ();
110 tree_->setInputCloud (cloud);
111 tree_->addPointsFromInputCloud ();
112 input_ = cloud;
113 }
114
115 /** \brief Provide a pointer to the input dataset.
116 * \param[in] cloud the const boost shared pointer to a PointCloud message
117 * \param[in] indices the point indices subset that is to be used from \a cloud
118 */
119 inline void
120 setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr& indices) override
121 {
122 tree_->deleteTree ();
123 tree_->setInputCloud (cloud, indices);
124 tree_->addPointsFromInputCloud ();
125 input_ = cloud;
126 indices_ = indices;
127 }
128
129 /** \brief Search for the k-nearest neighbors for the given query point.
130 * \param[in] cloud the point cloud data
131 * \param[in] index the index in \a cloud representing the query point
132 * \param[in] k the number of neighbors to search for
133 * \param[out] k_indices the resultant indices of the neighboring points (must be resized to \a k a priori!)
134 * \param[out] k_sqr_distances the resultant squared distances to the neighboring points (must be resized to \a k
135 * a priori!)
136 * \return number of neighbors found
137 */
138 inline int
139 nearestKSearch (const PointCloud &cloud, index_t index, int k, Indices &k_indices,
140 std::vector<float> &k_sqr_distances) const override
141 {
142 return (tree_->nearestKSearch (cloud, index, k, k_indices, k_sqr_distances));
143 }
144
145 /** \brief Search for the k-nearest neighbors for the given query point.
146 * \param[in] point the given query point
147 * \param[in] k the number of neighbors to search for
148 * \param[out] k_indices the resultant indices of the neighboring points (must be resized to \a k a priori!)
149 * \param[out] k_sqr_distances the resultant squared distances to the neighboring points (must be resized to \a k
150 * a priori!)
151 * \return number of neighbors found
152 */
153 inline int
154 nearestKSearch (const PointT &point, int k, Indices &k_indices,
155 std::vector<float> &k_sqr_distances) const override
156 {
157 return (tree_->nearestKSearch (point, k, k_indices, k_sqr_distances));
158 }
159
160 /** \brief Search for the k-nearest neighbors for the given query point (zero-copy).
161 *
162 * \param[in] index the index representing the query point in the
163 * dataset given by \a setInputCloud if indices were given in
164 * setInputCloud, index will be the position in the indices vector
165 * \param[in] k the number of neighbors to search for
166 * \param[out] k_indices the resultant indices of the neighboring points (must be resized to \a k a priori!)
167 * \param[out] k_sqr_distances the resultant squared distances to the neighboring points (must be resized to \a k
168 * a priori!)
169 * \return number of neighbors found
170 */
171 inline int
172 nearestKSearch (index_t index, int k, Indices &k_indices, std::vector<float> &k_sqr_distances) const override
173 {
174 return (tree_->nearestKSearch (index, k, k_indices, k_sqr_distances));
175 }
176
177 /** \brief search for all neighbors of query point that are within a given radius.
178 * \param cloud the point cloud data
179 * \param index the index in \a cloud representing the query point
180 * \param radius the radius of the sphere bounding all of p_q's neighbors
181 * \param k_indices the resultant indices of the neighboring points
182 * \param k_sqr_distances the resultant squared distances to the neighboring points
183 * \param max_nn if given, bounds the maximum returned neighbors to this value
184 * \return number of neighbors found in radius
185 */
186 inline int
187 radiusSearch (const PointCloud &cloud,
188 index_t index,
189 double radius,
190 Indices &k_indices,
191 std::vector<float> &k_sqr_distances,
192 unsigned int max_nn = 0) const override
193 {
194 tree_->radiusSearch (cloud, index, radius, k_indices, k_sqr_distances, max_nn);
195 if (sorted_results_)
196 this->sortResults (k_indices, k_sqr_distances);
197 return (static_cast<int> (k_indices.size ()));
198 }
199
200 /** \brief search for all neighbors of query point that are within a given radius.
201 * \param p_q the given query point
202 * \param radius the radius of the sphere bounding all of p_q's neighbors
203 * \param k_indices the resultant indices of the neighboring points
204 * \param k_sqr_distances the resultant squared distances to the neighboring points
205 * \param max_nn if given, bounds the maximum returned neighbors to this value
206 * \return number of neighbors found in radius
207 */
208 inline int
209 radiusSearch (const PointT &p_q,
210 double radius,
211 Indices &k_indices,
212 std::vector<float> &k_sqr_distances,
213 unsigned int max_nn = 0) const override
214 {
215 tree_->radiusSearch (p_q, radius, k_indices, k_sqr_distances, max_nn);
216 if (sorted_results_)
217 this->sortResults (k_indices, k_sqr_distances);
218 return (static_cast<int> (k_indices.size ()));
219 }
220
221 /** \brief search for all neighbors of query point that are within a given radius.
222 * \param index index representing the query point in the dataset given by \a setInputCloud.
223 * If indices were given in setInputCloud, index will be the position in the indices vector
224 * \param radius radius of the sphere bounding all of p_q's neighbors
225 * \param k_indices the resultant indices of the neighboring points
226 * \param k_sqr_distances the resultant squared distances to the neighboring points
227 * \param max_nn if given, bounds the maximum returned neighbors to this value
228 * \return number of neighbors found in radius
229 */
230 inline int
231 radiusSearch (index_t index, double radius, Indices &k_indices,
232 std::vector<float> &k_sqr_distances, unsigned int max_nn = 0) const override
233 {
234 tree_->radiusSearch (index, radius, k_indices, k_sqr_distances, max_nn);
235 if (sorted_results_)
236 this->sortResults (k_indices, k_sqr_distances);
237 return (static_cast<int> (k_indices.size ()));
238 }
239
240
241 /** \brief Search for approximate nearest neighbor at the query point.
242 * \param[in] cloud the point cloud data
243 * \param[in] query_index the index in \a cloud representing the query point
244 * \param[out] result_index the resultant index of the neighbor point
245 * \param[out] sqr_distance the resultant squared distance to the neighboring point
246 * \return number of neighbors found
247 */
248 inline void
249 approxNearestSearch (const PointCloudConstPtr &cloud, index_t query_index, index_t &result_index,
250 float &sqr_distance)
251 {
252 return (tree_->approxNearestSearch ((*cloud)[query_index], result_index, sqr_distance));
253 }
254
255 /** \brief Search for approximate nearest neighbor at the query point.
256 * \param[in] p_q the given query point
257 * \param[out] result_index the resultant index of the neighbor point
258 * \param[out] sqr_distance the resultant squared distance to the neighboring point
259 */
260 inline void
261 approxNearestSearch (const PointT &p_q, index_t &result_index, float &sqr_distance)
262 {
263 return (tree_->approxNearestSearch (p_q, result_index, sqr_distance));
264 }
265
266 /** \brief Search for approximate nearest neighbor at the query point.
267 * \param query_index index representing the query point in the dataset given by \a setInputCloud.
268 * If indices were given in setInputCloud, index will be the position in the indices vector.
269 * \param result_index the resultant index of the neighbor point
270 * \param sqr_distance the resultant squared distance to the neighboring point
271 * \return number of neighbors found
272 */
273 inline void
274 approxNearestSearch (index_t query_index, index_t &result_index, float &sqr_distance)
275 {
276 return (tree_->approxNearestSearch (query_index, result_index, sqr_distance));
277 }
278 /** \brief Search for points within rectangular search area
279 * \param[in] min_pt lower corner of search area
280 * \param[in] max_pt upper corner of search area
281 * \param[out] k_indices the resultant point indices
282 * \return number of points found within search area
283 */
284 inline uindex_t
285 boxSearch(const Eigen::Vector3f &min_pt, const Eigen::Vector3f &max_pt, Indices &k_indices) const
286 {
287 return (tree_->boxSearch(min_pt, max_pt, k_indices));
288 }
289 };
290 }
291}
292
293#ifdef PCL_NO_PRECOMPILE
294#include <pcl/octree/impl/octree_search.hpp>
295#else
296#define PCL_INSTANTIATE_Octree(T) template class PCL_EXPORTS pcl::search::Octree<T>;
297#endif
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
Octree container class that does not store any information.
Octree container class that does store a vector of point indices.
shared_ptr< const OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT > > ConstPtr
Definition: octree_search.h:72
shared_ptr< OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT > > Ptr
Definition: octree_search.h:70
search::Octree is a wrapper class which implements nearest neighbor search operations based on the pc...
Definition: octree.h:69
shared_ptr< const pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT > > ConstPtr
Definition: octree.h:73
void setInputCloud(const PointCloudConstPtr &cloud, const IndicesConstPtr &indices) override
Provide a pointer to the input dataset.
Definition: octree.h:120
uindex_t boxSearch(const Eigen::Vector3f &min_pt, const Eigen::Vector3f &max_pt, Indices &k_indices) const
Search for points within rectangular search area.
Definition: octree.h:285
typename PointCloud::Ptr PointCloudPtr
Definition: octree.h:76
int nearestKSearch(index_t index, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const override
Search for the k-nearest neighbors for the given query point (zero-copy).
Definition: octree.h:172
void setInputCloud(const PointCloudConstPtr &cloud)
Provide a pointer to the input dataset.
Definition: octree.h:107
~Octree()
Empty Destructor.
Definition: octree.h:99
int radiusSearch(const PointT &p_q, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const override
search for all neighbors of query point that are within a given radius.
Definition: octree.h:209
OctreePointCloudSearchPtr tree_
Definition: octree.h:82
void approxNearestSearch(const PointCloudConstPtr &cloud, index_t query_index, index_t &result_index, float &sqr_distance)
Search for approximate nearest neighbor at the query point.
Definition: octree.h:249
typename PointCloud::ConstPtr PointCloudConstPtr
Definition: octree.h:77
int radiusSearch(index_t index, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const override
search for all neighbors of query point that are within a given radius.
Definition: octree.h:231
typename pcl::octree::OctreePointCloudSearch< PointT, LeafTWrap, BranchTWrap >::ConstPtr OctreePointCloudSearchConstPtr
Definition: octree.h:81
void approxNearestSearch(index_t query_index, index_t &result_index, float &sqr_distance)
Search for approximate nearest neighbor at the query point.
Definition: octree.h:274
Octree(const double resolution)
Octree constructor.
Definition: octree.h:91
int radiusSearch(const PointCloud &cloud, index_t index, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const override
search for all neighbors of query point that are within a given radius.
Definition: octree.h:187
typename pcl::octree::OctreePointCloudSearch< PointT, LeafTWrap, BranchTWrap >::Ptr OctreePointCloudSearchPtr
Definition: octree.h:80
shared_ptr< pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT > > Ptr
Definition: octree.h:72
void approxNearestSearch(const PointT &p_q, index_t &result_index, float &sqr_distance)
Search for approximate nearest neighbor at the query point.
Definition: octree.h:261
int nearestKSearch(const PointT &point, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const override
Search for the k-nearest neighbors for the given query point.
Definition: octree.h:154
int nearestKSearch(const PointCloud &cloud, index_t index, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const override
Search for the k-nearest neighbors for the given query point.
Definition: octree.h:139
Generic search class.
Definition: search.h:75
PointCloudConstPtr input_
Definition: search.h:403
void sortResults(Indices &indices, std::vector< float > &distances) const
Definition: search.hpp:188
IndicesConstPtr indices_
Definition: search.h:404
pcl::IndicesConstPtr IndicesConstPtr
Definition: search.h:85
bool sorted_results_
Definition: search.h:405
detail::int_type_t< detail::index_type_size, false > uindex_t
Type used for an unsigned index in PCL.
Definition: types.h:120
detail::int_type_t< detail::index_type_size, detail::index_type_signed > index_t
Type used for an index in PCL.
Definition: types.h:112
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133
A point structure representing Euclidean xyz coordinates, and the RGB color.