Point Cloud Library (PCL)  1.11.1-dev
integral_image_normal.h
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38 
39 #pragma once
40 
41 #include <pcl/memory.h>
42 #include <pcl/pcl_macros.h>
43 #include <pcl/point_cloud.h>
44 #include <pcl/features/feature.h>
45 #include <pcl/features/integral_image2D.h>
46 
47 namespace pcl
48 {
49  /** \brief Surface normal estimation on organized data using integral images.
50  *
51  * For detailed information about this method see:
52  *
53  * S. Holzer and R. B. Rusu and M. Dixon and S. Gedikli and N. Navab,
54  * Adaptive Neighborhood Selection for Real-Time Surface Normal Estimation
55  * from Organized Point Cloud Data Using Integral Images, IROS 2012.
56  *
57  * D. Holz, S. Holzer, R. B. Rusu, and S. Behnke (2011, July).
58  * Real-Time Plane Segmentation using RGB-D Cameras. In Proceedings of
59  * the 15th RoboCup International Symposium, Istanbul, Turkey.
60  * http://www.ais.uni-bonn.de/~holz/papers/holz_2011_robocup.pdf
61  *
62  * \author Stefan Holzer
63  */
64  template <typename PointInT, typename PointOutT>
65  class IntegralImageNormalEstimation: public Feature<PointInT, PointOutT>
66  {
72 
73  public:
74  using Ptr = shared_ptr<IntegralImageNormalEstimation<PointInT, PointOutT> >;
75  using ConstPtr = shared_ptr<const IntegralImageNormalEstimation<PointInT, PointOutT> >;
76 
77  /** \brief Different types of border handling. */
79  {
82  };
83 
84  /** \brief Different normal estimation methods.
85  * <ul>
86  * <li><b>COVARIANCE_MATRIX</b> - creates 9 integral images to compute the normal for a specific point
87  * from the covariance matrix of its local neighborhood.</li>
88  * <li><b>AVERAGE_3D_GRADIENT</b> - creates 6 integral images to compute smoothed versions of
89  * horizontal and vertical 3D gradients and computes the normals using the cross-product between these
90  * two gradients.
91  * <li><b>AVERAGE_DEPTH_CHANGE</b> - creates only a single integral image and computes the normals
92  * from the average depth changes.
93  * </ul>
94  */
96  {
101  };
102 
105 
106  /** \brief Constructor */
108  : normal_estimation_method_(AVERAGE_3D_GRADIENT)
109  , border_policy_ (BORDER_POLICY_IGNORE)
110  , rect_width_ (0), rect_width_2_ (0), rect_width_4_ (0)
111  , rect_height_ (0), rect_height_2_ (0), rect_height_4_ (0)
112  , distance_threshold_ (0)
113  , integral_image_DX_ (false)
114  , integral_image_DY_ (false)
115  , integral_image_depth_ (false)
116  , integral_image_XYZ_ (true)
117  , diff_x_ (nullptr)
118  , diff_y_ (nullptr)
119  , depth_data_ (nullptr)
120  , distance_map_ (nullptr)
121  , use_depth_dependent_smoothing_ (false)
122  , max_depth_change_factor_ (20.0f*0.001f)
123  , normal_smoothing_size_ (10.0f)
124  , init_covariance_matrix_ (false)
125  , init_average_3d_gradient_ (false)
126  , init_simple_3d_gradient_ (false)
127  , init_depth_change_ (false)
128  , vpx_ (0.0f)
129  , vpy_ (0.0f)
130  , vpz_ (0.0f)
131  , use_sensor_origin_ (true)
132  {
133  feature_name_ = "IntegralImagesNormalEstimation";
134  tree_.reset ();
135  k_ = 1;
136  }
137 
138  /** \brief Destructor **/
140 
141  /** \brief Set the regions size which is considered for normal estimation.
142  * \param[in] width the width of the search rectangle
143  * \param[in] height the height of the search rectangle
144  */
145  void
146  setRectSize (const int width, const int height);
147 
148  /** \brief Sets the policy for handling borders.
149  * \param[in] border_policy the border policy.
150  */
151  void
152  setBorderPolicy (const BorderPolicy border_policy)
153  {
154  border_policy_ = border_policy;
155  }
156 
157  /** \brief Computes the normal at the specified position.
158  * \param[in] pos_x x position (pixel)
159  * \param[in] pos_y y position (pixel)
160  * \param[in] point_index the position index of the point
161  * \param[out] normal the output estimated normal
162  */
163  void
164  computePointNormal (const int pos_x, const int pos_y, const unsigned point_index, PointOutT &normal);
165 
166  /** \brief Computes the normal at the specified position with mirroring for border handling.
167  * \param[in] pos_x x position (pixel)
168  * \param[in] pos_y y position (pixel)
169  * \param[in] point_index the position index of the point
170  * \param[out] normal the output estimated normal
171  */
172  void
173  computePointNormalMirror (const int pos_x, const int pos_y, const unsigned point_index, PointOutT &normal);
174 
175  /** \brief The depth change threshold for computing object borders
176  * \param[in] max_depth_change_factor the depth change threshold for computing object borders based on
177  * depth changes
178  */
179  void
180  setMaxDepthChangeFactor (float max_depth_change_factor)
181  {
182  max_depth_change_factor_ = max_depth_change_factor;
183  }
184 
185  /** \brief Set the normal smoothing size
186  * \param[in] normal_smoothing_size factor which influences the size of the area used to smooth normals
187  * (depth dependent if useDepthDependentSmoothing is true)
188  */
189  void
190  setNormalSmoothingSize (float normal_smoothing_size)
191  {
192  if (normal_smoothing_size <= 0)
193  {
194  PCL_ERROR ("[pcl::%s::setNormalSmoothingSize] Invalid normal smoothing size given! (%f). Allowed ranges are: 0 < N. Defaulting to %f.\n",
195  feature_name_.c_str (), normal_smoothing_size, normal_smoothing_size_);
196  return;
197  }
198  normal_smoothing_size_ = normal_smoothing_size;
199  }
200 
201  /** \brief Set the normal estimation method. The current implemented algorithms are:
202  * <ul>
203  * <li><b>COVARIANCE_MATRIX</b> - creates 9 integral images to compute the normal for a specific point
204  * from the covariance matrix of its local neighborhood.</li>
205  * <li><b>AVERAGE_3D_GRADIENT</b> - creates 6 integral images to compute smoothed versions of
206  * horizontal and vertical 3D gradients and computes the normals using the cross-product between these
207  * two gradients.
208  * <li><b>AVERAGE_DEPTH_CHANGE</b> - creates only a single integral image and computes the normals
209  * from the average depth changes.
210  * </ul>
211  * \param[in] normal_estimation_method the method used for normal estimation
212  */
213  void
215  {
216  normal_estimation_method_ = normal_estimation_method;
217  }
218 
219  /** \brief Set whether to use depth depending smoothing or not
220  * \param[in] use_depth_dependent_smoothing decides whether the smoothing is depth dependent
221  */
222  void
223  setDepthDependentSmoothing (bool use_depth_dependent_smoothing)
224  {
225  use_depth_dependent_smoothing_ = use_depth_dependent_smoothing;
226  }
227 
228  /** \brief Provide a pointer to the input dataset (overwrites the PCLBase::setInputCloud method)
229  * \param[in] cloud the const boost shared pointer to a PointCloud message
230  */
231  inline void
232  setInputCloud (const typename PointCloudIn::ConstPtr &cloud) override
233  {
234  input_ = cloud;
235  if (!cloud->isOrganized ())
236  {
237  PCL_ERROR ("[pcl::IntegralImageNormalEstimation::setInputCloud] Input dataset is not organized (height = 1).\n");
238  return;
239  }
240 
241  init_covariance_matrix_ = init_average_3d_gradient_ = init_depth_change_ = false;
242 
243  if (use_sensor_origin_)
244  {
245  vpx_ = input_->sensor_origin_.coeff (0);
246  vpy_ = input_->sensor_origin_.coeff (1);
247  vpz_ = input_->sensor_origin_.coeff (2);
248  }
249 
250  // Initialize the correct data structure based on the normal estimation method chosen
251  initData ();
252  }
253 
254  /** \brief Returns a pointer to the distance map which was computed internally
255  */
256  inline float*
258  {
259  return (distance_map_);
260  }
261 
262  /** \brief Set the viewpoint.
263  * \param vpx the X coordinate of the viewpoint
264  * \param vpy the Y coordinate of the viewpoint
265  * \param vpz the Z coordinate of the viewpoint
266  */
267  inline void
268  setViewPoint (float vpx, float vpy, float vpz)
269  {
270  vpx_ = vpx;
271  vpy_ = vpy;
272  vpz_ = vpz;
273  use_sensor_origin_ = false;
274  }
275 
276  /** \brief Get the viewpoint.
277  * \param [out] vpx x-coordinate of the view point
278  * \param [out] vpy y-coordinate of the view point
279  * \param [out] vpz z-coordinate of the view point
280  * \note this method returns the currently used viewpoint for normal flipping.
281  * If the viewpoint is set manually using the setViewPoint method, this method will return the set view point coordinates.
282  * If an input cloud is set, it will return the sensor origin otherwise it will return the origin (0, 0, 0)
283  */
284  inline void
285  getViewPoint (float &vpx, float &vpy, float &vpz)
286  {
287  vpx = vpx_;
288  vpy = vpy_;
289  vpz = vpz_;
290  }
291 
292  /** \brief sets whether the sensor origin or a user given viewpoint should be used. After this method, the
293  * normal estimation method uses the sensor origin of the input cloud.
294  * to use a user defined view point, use the method setViewPoint
295  */
296  inline void
298  {
299  use_sensor_origin_ = true;
300  if (input_)
301  {
302  vpx_ = input_->sensor_origin_.coeff (0);
303  vpy_ = input_->sensor_origin_.coeff (1);
304  vpz_ = input_->sensor_origin_.coeff (2);
305  }
306  else
307  {
308  vpx_ = 0;
309  vpy_ = 0;
310  vpz_ = 0;
311  }
312  }
313 
314  protected:
315 
316  /** \brief Computes the normal for the complete cloud or only \a indices_ if provided.
317  * \param[out] output the resultant normals
318  */
319  void
320  computeFeature (PointCloudOut &output) override;
321 
322  /** \brief Computes the normal for the complete cloud.
323  * \param[in] distance_map distance map
324  * \param[in] bad_point constant given to invalid normal components
325  * \param[out] output the resultant normals
326  */
327  void
328  computeFeatureFull (const float* distance_map, const float& bad_point, PointCloudOut& output);
329 
330  /** \brief Computes the normal for part of the cloud specified by \a indices_
331  * \param[in] distance_map distance map
332  * \param[in] bad_point constant given to invalid normal components
333  * \param[out] output the resultant normals
334  */
335  void
336  computeFeaturePart (const float* distance_map, const float& bad_point, PointCloudOut& output);
337 
338  /** \brief Initialize the data structures, based on the normal estimation method chosen. */
339  void
340  initData ();
341 
342  private:
343 
344  /** \brief Flip (in place) the estimated normal of a point towards a given viewpoint
345  * \param point a given point
346  * \param vp_x the X coordinate of the viewpoint
347  * \param vp_y the X coordinate of the viewpoint
348  * \param vp_z the X coordinate of the viewpoint
349  * \param nx the resultant X component of the plane normal
350  * \param ny the resultant Y component of the plane normal
351  * \param nz the resultant Z component of the plane normal
352  * \ingroup features
353  */
354  inline void
355  flipNormalTowardsViewpoint (const PointInT &point,
356  float vp_x, float vp_y, float vp_z,
357  float &nx, float &ny, float &nz)
358  {
359  // See if we need to flip any plane normals
360  vp_x -= point.x;
361  vp_y -= point.y;
362  vp_z -= point.z;
363 
364  // Dot product between the (viewpoint - point) and the plane normal
365  float cos_theta = (vp_x * nx + vp_y * ny + vp_z * nz);
366 
367  // Flip the plane normal
368  if (cos_theta < 0)
369  {
370  nx *= -1;
371  ny *= -1;
372  nz *= -1;
373  }
374  }
375 
376  /** \brief The normal estimation method to use. Currently, 3 implementations are provided:
377  *
378  * - COVARIANCE_MATRIX
379  * - AVERAGE_3D_GRADIENT
380  * - AVERAGE_DEPTH_CHANGE
381  */
382  NormalEstimationMethod normal_estimation_method_;
383 
384  /** \brief The policy for handling borders. */
385  BorderPolicy border_policy_;
386 
387  /** The width of the neighborhood region used for computing the normal. */
388  int rect_width_;
389  int rect_width_2_;
390  int rect_width_4_;
391  /** The height of the neighborhood region used for computing the normal. */
392  int rect_height_;
393  int rect_height_2_;
394  int rect_height_4_;
395 
396  /** the threshold used to detect depth discontinuities */
397  float distance_threshold_;
398 
399  /** integral image in x-direction */
400  IntegralImage2D<float, 3> integral_image_DX_;
401  /** integral image in y-direction */
402  IntegralImage2D<float, 3> integral_image_DY_;
403  /** integral image */
404  IntegralImage2D<float, 1> integral_image_depth_;
405  /** integral image xyz */
406  IntegralImage2D<float, 3> integral_image_XYZ_;
407 
408  /** derivatives in x-direction */
409  float *diff_x_;
410  /** derivatives in y-direction */
411  float *diff_y_;
412 
413  /** depth data */
414  float *depth_data_;
415 
416  /** distance map */
417  float *distance_map_;
418 
419  /** \brief Smooth data based on depth (true/false). */
420  bool use_depth_dependent_smoothing_;
421 
422  /** \brief Threshold for detecting depth discontinuities */
423  float max_depth_change_factor_;
424 
425  /** \brief */
426  float normal_smoothing_size_;
427 
428  /** \brief True when a dataset has been received and the covariance_matrix data has been initialized. */
429  bool init_covariance_matrix_;
430 
431  /** \brief True when a dataset has been received and the average 3d gradient data has been initialized. */
432  bool init_average_3d_gradient_;
433 
434  /** \brief True when a dataset has been received and the simple 3d gradient data has been initialized. */
435  bool init_simple_3d_gradient_;
436 
437  /** \brief True when a dataset has been received and the depth change data has been initialized. */
438  bool init_depth_change_;
439 
440  /** \brief Values describing the viewpoint ("pinhole" camera model assumed). For per point viewpoints, inherit
441  * from NormalEstimation and provide your own computeFeature (). By default, the viewpoint is set to 0,0,0. */
442  float vpx_, vpy_, vpz_;
443 
444  /** whether the sensor origin of the input cloud or a user given viewpoint should be used.*/
445  bool use_sensor_origin_;
446 
447  /** \brief This method should get called before starting the actual computation. */
448  bool
449  initCompute () override;
450 
451  /** \brief Internal initialization method for COVARIANCE_MATRIX estimation. */
452  void
453  initCovarianceMatrixMethod ();
454 
455  /** \brief Internal initialization method for AVERAGE_3D_GRADIENT estimation. */
456  void
457  initAverage3DGradientMethod ();
458 
459  /** \brief Internal initialization method for AVERAGE_DEPTH_CHANGE estimation. */
460  void
461  initAverageDepthChangeMethod ();
462 
463  /** \brief Internal initialization method for SIMPLE_3D_GRADIENT estimation. */
464  void
465  initSimple3DGradientMethod ();
466 
467  public:
469  };
470 }
471 
472 #ifdef PCL_NO_PRECOMPILE
473 #include <pcl/features/impl/integral_image_normal.hpp>
474 #endif
pcl_macros.h
Defines all the PCL and non-PCL macros used.
pcl::IntegralImageNormalEstimation::initData
void initData()
Initialize the data structures, based on the normal estimation method chosen.
Definition: integral_image_normal.hpp:56
pcl
Definition: convolution.h:46
pcl::Feature< pcl::PointXYZRGBA, pcl::Normal >::Ptr
shared_ptr< Feature< pcl::PointXYZRGBA, pcl::Normal > > Ptr
Definition: feature.h:114
pcl::IntegralImageNormalEstimation::useSensorOriginAsViewPoint
void useSensorOriginAsViewPoint()
sets whether the sensor origin or a user given viewpoint should be used.
Definition: integral_image_normal.h:297
pcl::IntegralImageNormalEstimation::computeFeatureFull
void computeFeatureFull(const float *distance_map, const float &bad_point, PointCloudOut &output)
Computes the normal for the complete cloud.
Definition: integral_image_normal.hpp:838
pcl::PCLBase< PointInT >::input_
PointCloudConstPtr input_
The input point cloud dataset.
Definition: pcl_base.h:147
pcl::IntegralImageNormalEstimation::SIMPLE_3D_GRADIENT
@ SIMPLE_3D_GRADIENT
Definition: integral_image_normal.h:100
pcl::IntegralImageNormalEstimation
Surface normal estimation on organized data using integral images.
Definition: integral_image_normal.h:65
pcl::IntegralImageNormalEstimation::PointCloudOut
typename Feature< PointInT, PointOutT >::PointCloudOut PointCloudOut
Definition: integral_image_normal.h:104
pcl::IntegralImageNormalEstimation::computeFeature
void computeFeature(PointCloudOut &output) override
Computes the normal for the complete cloud or only indices_ if provided.
Definition: integral_image_normal.hpp:731
pcl::IntegralImageNormalEstimation::computeFeaturePart
void computeFeaturePart(const float *distance_map, const float &bad_point, PointCloudOut &output)
Computes the normal for part of the cloud specified by indices_.
Definition: integral_image_normal.hpp:1025
pcl::PointCloud< pcl::PointXYZRGBA >
pcl::IntegralImageNormalEstimation::setInputCloud
void setInputCloud(const typename PointCloudIn::ConstPtr &cloud) override
Provide a pointer to the input dataset (overwrites the PCLBase::setInputCloud method)
Definition: integral_image_normal.h:232
pcl::IntegralImageNormalEstimation::setNormalEstimationMethod
void setNormalEstimationMethod(NormalEstimationMethod normal_estimation_method)
Set the normal estimation method.
Definition: integral_image_normal.h:214
pcl::IntegralImageNormalEstimation::BorderPolicy
BorderPolicy
Different types of border handling.
Definition: integral_image_normal.h:78
pcl::Feature< pcl::PointXYZRGBA, pcl::Normal >::ConstPtr
shared_ptr< const Feature< pcl::PointXYZRGBA, pcl::Normal > > ConstPtr
Definition: feature.h:115
pcl::IntegralImageNormalEstimation::setViewPoint
void setViewPoint(float vpx, float vpy, float vpz)
Set the viewpoint.
Definition: integral_image_normal.h:268
pcl::IntegralImageNormalEstimation::getDistanceMap
float * getDistanceMap()
Returns a pointer to the distance map which was computed internally.
Definition: integral_image_normal.h:257
pcl::IntegralImageNormalEstimation::setDepthDependentSmoothing
void setDepthDependentSmoothing(bool use_depth_dependent_smoothing)
Set whether to use depth depending smoothing or not.
Definition: integral_image_normal.h:223
pcl::IntegralImageNormalEstimation::BORDER_POLICY_MIRROR
@ BORDER_POLICY_MIRROR
Definition: integral_image_normal.h:81
pcl::Feature::tree_
KdTreePtr tree_
A pointer to the spatial search object.
Definition: feature.h:234
pcl::IntegralImageNormalEstimation::setNormalSmoothingSize
void setNormalSmoothingSize(float normal_smoothing_size)
Set the normal smoothing size.
Definition: integral_image_normal.h:190
pcl::IntegralImageNormalEstimation::AVERAGE_DEPTH_CHANGE
@ AVERAGE_DEPTH_CHANGE
Definition: integral_image_normal.h:99
pcl::IntegralImageNormalEstimation::NormalEstimationMethod
NormalEstimationMethod
Different normal estimation methods.
Definition: integral_image_normal.h:95
pcl::IntegralImageNormalEstimation::BORDER_POLICY_IGNORE
@ BORDER_POLICY_IGNORE
Definition: integral_image_normal.h:80
pcl::IntegralImageNormalEstimation::~IntegralImageNormalEstimation
~IntegralImageNormalEstimation()
Destructor.
Definition: integral_image_normal.hpp:46
PCL_MAKE_ALIGNED_OPERATOR_NEW
#define PCL_MAKE_ALIGNED_OPERATOR_NEW
Macro to signal a class requires a custom allocator.
Definition: memory.h:63
pcl::IntegralImageNormalEstimation::computePointNormalMirror
void computePointNormalMirror(const int pos_x, const int pos_y, const unsigned point_index, PointOutT &normal)
Computes the normal at the specified position with mirroring for border handling.
Definition: integral_image_normal.hpp:462
pcl::Feature::k_
int k_
The number of K nearest neighbors to use for each point.
Definition: feature.h:243
pcl::IntegralImageNormalEstimation::computePointNormal
void computePointNormal(const int pos_x, const int pos_y, const unsigned point_index, PointOutT &normal)
Computes the normal at the specified position.
Definition: integral_image_normal.hpp:207
pcl::IntegralImageNormalEstimation::IntegralImageNormalEstimation
IntegralImageNormalEstimation()
Constructor.
Definition: integral_image_normal.h:107
pcl::PointCloud< pcl::PointXYZRGBA >::ConstPtr
shared_ptr< const PointCloud< pcl::PointXYZRGBA > > ConstPtr
Definition: point_cloud.h:408
pcl::IntegralImageNormalEstimation::AVERAGE_3D_GRADIENT
@ AVERAGE_3D_GRADIENT
Definition: integral_image_normal.h:98
pcl::IntegralImageNormalEstimation::getViewPoint
void getViewPoint(float &vpx, float &vpy, float &vpz)
Get the viewpoint.
Definition: integral_image_normal.h:285
pcl::IntegralImageNormalEstimation::setBorderPolicy
void setBorderPolicy(const BorderPolicy border_policy)
Sets the policy for handling borders.
Definition: integral_image_normal.h:152
pcl::Feature::feature_name_
std::string feature_name_
The feature name.
Definition: feature.h:223
pcl::IntegralImageNormalEstimation::COVARIANCE_MATRIX
@ COVARIANCE_MATRIX
Definition: integral_image_normal.h:97
memory.h
Defines functions, macros and traits for allocating and using memory.
pcl::IntegralImageNormalEstimation::setRectSize
void setRectSize(const int width, const int height)
Set the regions size which is considered for normal estimation.
Definition: integral_image_normal.hpp:93
pcl::IntegralImageNormalEstimation::setMaxDepthChangeFactor
void setMaxDepthChangeFactor(float max_depth_change_factor)
The depth change threshold for computing object borders.
Definition: integral_image_normal.h:180
pcl::Feature
Feature represents the base feature class.
Definition: feature.h:106