Point Cloud Library (PCL)  1.7.0
sac_model_cone.h
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38 
39 #ifndef PCL_SAMPLE_CONSENSUS_MODEL_CONE_H_
40 #define PCL_SAMPLE_CONSENSUS_MODEL_CONE_H_
41 
42 #include <pcl/sample_consensus/sac_model.h>
43 #include <pcl/sample_consensus/model_types.h>
44 #include <pcl/common/common.h>
45 #include <pcl/common/distances.h>
46 #include <limits.h>
47 
48 namespace pcl
49 {
50  /** \brief @b SampleConsensusModelCone defines a model for 3D cone segmentation.
51  * The model coefficients are defined as:
52  * <ul>
53  * <li><b>apex.x</b> : the X coordinate of cone's apex
54  * <li><b>apex.y</b> : the Y coordinate of cone's apex
55  * <li><b>apex.z</b> : the Z coordinate of cone's apex
56  * <li><b>axis_direction.x</b> : the X coordinate of the cone's axis direction
57  * <li><b>axis_direction.y</b> : the Y coordinate of the cone's axis direction
58  * <li><b>axis_direction.z</b> : the Z coordinate of the cone's axis direction
59  * <li><b>opening_angle</b> : the cone's opening angle
60  * </ul>
61  * \author Stefan Schrandt
62  * \ingroup sample_consensus
63  */
64  template <typename PointT, typename PointNT>
65  class SampleConsensusModelCone : public SampleConsensusModel<PointT>, public SampleConsensusModelFromNormals<PointT, PointNT>
66  {
67  public:
75 
79 
80  typedef boost::shared_ptr<SampleConsensusModelCone> Ptr;
81 
82  /** \brief Constructor for base SampleConsensusModelCone.
83  * \param[in] cloud the input point cloud dataset
84  * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
85  */
86  SampleConsensusModelCone (const PointCloudConstPtr &cloud, bool random = false)
87  : SampleConsensusModel<PointT> (cloud, random)
89  , axis_ (Eigen::Vector3f::Zero ())
90  , eps_angle_ (0)
91  , min_angle_ (-std::numeric_limits<double>::max ())
92  , max_angle_ (std::numeric_limits<double>::max ())
93  , tmp_inliers_ ()
94  {
95  }
96 
97  /** \brief Constructor for base SampleConsensusModelCone.
98  * \param[in] cloud the input point cloud dataset
99  * \param[in] indices a vector of point indices to be used from \a cloud
100  * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
101  */
103  const std::vector<int> &indices,
104  bool random = false)
105  : SampleConsensusModel<PointT> (cloud, indices, random)
107  , axis_ (Eigen::Vector3f::Zero ())
108  , eps_angle_ (0)
109  , min_angle_ (-std::numeric_limits<double>::max ())
110  , max_angle_ (std::numeric_limits<double>::max ())
111  , tmp_inliers_ ()
112  {
113  }
114 
115  /** \brief Copy constructor.
116  * \param[in] source the model to copy into this
117  */
121  axis_ (), eps_angle_ (), min_angle_ (), max_angle_ (), tmp_inliers_ ()
122  {
123  *this = source;
124  }
125 
126  /** \brief Empty destructor */
128 
129  /** \brief Copy constructor.
130  * \param[in] source the model to copy into this
131  */
134  {
136  axis_ = source.axis_;
137  eps_angle_ = source.eps_angle_;
138  min_angle_ = source.min_angle_;
139  max_angle_ = source.max_angle_;
140  tmp_inliers_ = source.tmp_inliers_;
141  return (*this);
142  }
143 
144  /** \brief Set the angle epsilon (delta) threshold.
145  * \param[in] ea the maximum allowed difference between the cone's axis and the given axis.
146  */
147  inline void
148  setEpsAngle (double ea) { eps_angle_ = ea; }
149 
150  /** \brief Get the angle epsilon (delta) threshold. */
151  inline double
152  getEpsAngle () const { return (eps_angle_); }
153 
154  /** \brief Set the axis along which we need to search for a cone direction.
155  * \param[in] ax the axis along which we need to search for a cone direction
156  */
157  inline void
158  setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
159 
160  /** \brief Get the axis along which we need to search for a cone direction. */
161  inline Eigen::Vector3f
162  getAxis () const { return (axis_); }
163 
164  /** \brief Set the minimum and maximum allowable opening angle for a cone model
165  * given from a user.
166  * \param[in] min_angle the minimum allwoable opening angle of a cone model
167  * \param[in] max_angle the maximum allwoable opening angle of a cone model
168  */
169  inline void
170  setMinMaxOpeningAngle (const double &min_angle, const double &max_angle)
171  {
172  min_angle_ = min_angle;
173  max_angle_ = max_angle;
174  }
175 
176  /** \brief Get the opening angle which we need minumum to validate a cone model.
177  * \param[out] min_angle the minimum allwoable opening angle of a cone model
178  * \param[out] max_angle the maximum allwoable opening angle of a cone model
179  */
180  inline void
181  getMinMaxOpeningAngle (double &min_angle, double &max_angle) const
182  {
183  min_angle = min_angle_;
184  max_angle = max_angle_;
185  }
186 
187  /** \brief Check whether the given index samples can form a valid cone model, compute the model coefficients
188  * from these samples and store them in model_coefficients. The cone coefficients are: apex,
189  * axis_direction, opening_angle.
190  * \param[in] samples the point indices found as possible good candidates for creating a valid model
191  * \param[out] model_coefficients the resultant model coefficients
192  */
193  bool
194  computeModelCoefficients (const std::vector<int> &samples,
195  Eigen::VectorXf &model_coefficients);
196 
197  /** \brief Compute all distances from the cloud data to a given cone model.
198  * \param[in] model_coefficients the coefficients of a cone model that we need to compute distances to
199  * \param[out] distances the resultant estimated distances
200  */
201  void
202  getDistancesToModel (const Eigen::VectorXf &model_coefficients,
203  std::vector<double> &distances);
204 
205  /** \brief Select all the points which respect the given model coefficients as inliers.
206  * \param[in] model_coefficients the coefficients of a cone model that we need to compute distances to
207  * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
208  * \param[out] inliers the resultant model inliers
209  */
210  void
211  selectWithinDistance (const Eigen::VectorXf &model_coefficients,
212  const double threshold,
213  std::vector<int> &inliers);
214 
215  /** \brief Count all the points which respect the given model coefficients as inliers.
216  *
217  * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
218  * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
219  * \return the resultant number of inliers
220  */
221  virtual int
222  countWithinDistance (const Eigen::VectorXf &model_coefficients,
223  const double threshold);
224 
225 
226  /** \brief Recompute the cone coefficients using the given inlier set and return them to the user.
227  * @note: these are the coefficients of the cone model after refinement (eg. after SVD)
228  * \param[in] inliers the data inliers found as supporting the model
229  * \param[in] model_coefficients the initial guess for the optimization
230  * \param[out] optimized_coefficients the resultant recomputed coefficients after non-linear optimization
231  */
232  void
233  optimizeModelCoefficients (const std::vector<int> &inliers,
234  const Eigen::VectorXf &model_coefficients,
235  Eigen::VectorXf &optimized_coefficients);
236 
237 
238  /** \brief Create a new point cloud with inliers projected onto the cone model.
239  * \param[in] inliers the data inliers that we want to project on the cone model
240  * \param[in] model_coefficients the coefficients of a cone model
241  * \param[out] projected_points the resultant projected points
242  * \param[in] copy_data_fields set to true if we need to copy the other data fields
243  */
244  void
245  projectPoints (const std::vector<int> &inliers,
246  const Eigen::VectorXf &model_coefficients,
247  PointCloud &projected_points,
248  bool copy_data_fields = true);
249 
250  /** \brief Verify whether a subset of indices verifies the given cone model coefficients.
251  * \param[in] indices the data indices that need to be tested against the cone model
252  * \param[in] model_coefficients the cone model coefficients
253  * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
254  */
255  bool
256  doSamplesVerifyModel (const std::set<int> &indices,
257  const Eigen::VectorXf &model_coefficients,
258  const double threshold);
259 
260  /** \brief Return an unique id for this model (SACMODEL_CONE). */
261  inline pcl::SacModel
262  getModelType () const { return (SACMODEL_CONE); }
263 
264  protected:
265  /** \brief Get the distance from a point to a line (represented by a point and a direction)
266  * \param[in] pt a point
267  * \param[in] model_coefficients the line coefficients (a point on the line, line direction)
268  */
269  double
270  pointToAxisDistance (const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients);
271 
272  /** \brief Get a string representation of the name of this class. */
273  std::string
274  getName () const { return ("SampleConsensusModelCone"); }
275 
276  protected:
277  /** \brief Check whether a model is valid given the user constraints.
278  * \param[in] model_coefficients the set of model coefficients
279  */
280  bool
281  isModelValid (const Eigen::VectorXf &model_coefficients);
282 
283  /** \brief Check if a sample of indices results in a good sample of points
284  * indices. Pure virtual.
285  * \param[in] samples the resultant index samples
286  */
287  bool
288  isSampleGood (const std::vector<int> &samples) const;
289 
290  private:
291  /** \brief The axis along which we need to search for a plane perpendicular to. */
292  Eigen::Vector3f axis_;
293 
294  /** \brief The maximum allowed difference between the plane normal and the given axis. */
295  double eps_angle_;
296 
297  /** \brief The minimum and maximum allowed opening angles of valid cone model. */
298  double min_angle_;
299  double max_angle_;
300 
301  /** \brief temporary pointer to a list of given indices for optimizeModelCoefficients () */
302  const std::vector<int> *tmp_inliers_;
303 
304 #if defined BUILD_Maintainer && defined __GNUC__ && __GNUC__ == 4 && __GNUC_MINOR__ > 3
305 #pragma GCC diagnostic ignored "-Weffc++"
306 #endif
307  /** \brief Functor for the optimization function */
308  struct OptimizationFunctor : pcl::Functor<float>
309  {
310  /** Functor constructor
311  * \param[in] m_data_points the number of data points to evaluate
312  * \param[in] estimator pointer to the estimator object
313  * \param[in] distance distance computation function pointer
314  */
315  OptimizationFunctor (int m_data_points, pcl::SampleConsensusModelCone<PointT, PointNT> *model) :
316  pcl::Functor<float> (m_data_points), model_ (model) {}
317 
318  /** Cost function to be minimized
319  * \param[in] x variables array
320  * \param[out] fvec resultant functions evaluations
321  * \return 0
322  */
323  int
324  operator() (const Eigen::VectorXf &x, Eigen::VectorXf &fvec) const
325  {
326  Eigen::Vector4f apex (x[0], x[1], x[2], 0);
327  Eigen::Vector4f axis_dir (x[3], x[4], x[5], 0);
328  float opening_angle = x[6];
329 
330  float apexdotdir = apex.dot (axis_dir);
331  float dirdotdir = 1.0f / axis_dir.dot (axis_dir);
332 
333  for (int i = 0; i < values (); ++i)
334  {
335  // dist = f - r
336  Eigen::Vector4f pt (model_->input_->points[(*model_->tmp_inliers_)[i]].x,
337  model_->input_->points[(*model_->tmp_inliers_)[i]].y,
338  model_->input_->points[(*model_->tmp_inliers_)[i]].z, 0);
339 
340  // Calculate the point's projection on the cone axis
341  float k = (pt.dot (axis_dir) - apexdotdir) * dirdotdir;
342  Eigen::Vector4f pt_proj = apex + k * axis_dir;
343 
344  // Calculate the actual radius of the cone at the level of the projected point
345  Eigen::Vector4f height = apex-pt_proj;
346  float actual_cone_radius = tanf (opening_angle) * height.norm ();
347 
348  fvec[i] = static_cast<float> (pcl::sqrPointToLineDistance (pt, apex, axis_dir) - actual_cone_radius * actual_cone_radius);
349  }
350  return (0);
351  }
352 
354  };
355 #if defined BUILD_Maintainer && defined __GNUC__ && __GNUC__ == 4 && __GNUC_MINOR__ > 3
356 #pragma GCC diagnostic warning "-Weffc++"
357 #endif
358  };
359 }
360 
361 #ifdef PCL_NO_PRECOMPILE
362 #include <pcl/sample_consensus/impl/sac_model_cone.hpp>
363 #endif
364 
365 #endif //#ifndef PCL_SAMPLE_CONSENSUS_MODEL_CONE_H_