Point Cloud Library (PCL)  1.13.0-dev
spin_image.hpp
1 /*
2  * Software License Agreement (BSD License)
3  *
4  * Point Cloud Library (PCL) - www.pointclouds.org
5  * Copyright (c) 2010-2012, 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 #ifndef PCL_FEATURES_IMPL_SPIN_IMAGE_H_
42 #define PCL_FEATURES_IMPL_SPIN_IMAGE_H_
43 
44 #include <limits>
45 #include <pcl/point_types.h>
46 #include <pcl/exceptions.h>
47 #include <pcl/features/spin_image.h>
48 #include <cmath>
49 
50 //////////////////////////////////////////////////////////////////////////////////////////////
51 template <typename PointInT, typename PointNT, typename PointOutT>
53  unsigned int image_width, double support_angle_cos, unsigned int min_pts_neighb) :
54  input_normals_ (), rotation_axes_cloud_ (),
55  is_angular_ (false), rotation_axis_ (), use_custom_axis_(false), use_custom_axes_cloud_ (false),
56  is_radial_ (false), support_angle_cos_ (support_angle_cos),
57  min_pts_neighb_ (min_pts_neighb)
58 {
59  if (0.0 > support_angle_cos || support_angle_cos > 1.0) { // may be permit negative cosine?
60  throw PCLException ("Cosine of support angle should be between 0 and 1", "spin_image.hpp", "SpinImageEstimation");
61  }
62  setImageWidth(image_width);
63 
64  feature_name_ = "SpinImageEstimation";
65 }
66 
67 
68 //////////////////////////////////////////////////////////////////////////////////////////////
69 template <typename PointInT, typename PointNT, typename PointOutT> Eigen::ArrayXXd
71 {
72  assert (image_width_ > 0);
73  assert (support_angle_cos_ <= 1.0 && support_angle_cos_ >= 0.0); // may be permit negative cosine?
74 
75  const Eigen::Vector3f origin_point ((*input_)[index].getVector3fMap ());
76 
77  Eigen::Vector3f origin_normal;
78  origin_normal =
79  input_normals_ ?
80  (*input_normals_)[index].getNormalVector3fMap () :
81  Eigen::Vector3f (); // just a placeholder; should never be used!
82 
83  const Eigen::Vector3f rotation_axis = use_custom_axis_ ?
84  rotation_axis_.getNormalVector3fMap () :
85  use_custom_axes_cloud_ ?
86  (*rotation_axes_cloud_)[index].getNormalVector3fMap () :
87  origin_normal;
88 
89  Eigen::ArrayXXd m_matrix (Eigen::ArrayXXd::Zero (image_width_+1, 2*image_width_+1));
90  Eigen::ArrayXXd m_averAngles (Eigen::ArrayXXd::Zero (image_width_+1, 2*image_width_+1));
91 
92  // OK, we are interested in the points of the cylinder of height 2*r and
93  // base radius r, where r = m_dBinSize * in_iImageWidth
94  // it can be embedded to the sphere of radius sqrt(2) * m_dBinSize * in_iImageWidth
95  // suppose that points are uniformly distributed, so we lose ~40%
96  // according to the volumes ratio
97  double bin_size = 0.0;
98  if (is_radial_)
99  bin_size = search_radius_ / image_width_;
100  else
101  bin_size = search_radius_ / image_width_ / sqrt(2.0);
102 
103  pcl::Indices nn_indices;
104  std::vector<float> nn_sqr_dists;
105  const int neighb_cnt = this->searchForNeighbors (index, search_radius_, nn_indices, nn_sqr_dists);
106  if (neighb_cnt < static_cast<int> (min_pts_neighb_))
107  {
108  throw PCLException (
109  "Too few points for spin image, use setMinPointCountInNeighbourhood() to decrease the threshold or use larger feature radius",
110  "spin_image.hpp", "computeSiForPoint");
111  }
112 
113  // for all neighbor points
114  for (int i_neigh = 0; i_neigh < neighb_cnt ; i_neigh++)
115  {
116  // first, skip the points with distant normals
117  double cos_between_normals = -2.0; // should be initialized if used
118  if (support_angle_cos_ > 0.0 || is_angular_) // not bogus
119  {
120  cos_between_normals = origin_normal.dot ((*input_normals_)[nn_indices[i_neigh]].getNormalVector3fMap ());
121  if (std::abs (cos_between_normals) > (1.0 + 10*std::numeric_limits<float>::epsilon ())) // should be okay for numeric stability
122  {
123  PCL_ERROR ("[pcl::%s::computeSiForPoint] Normal for the point %d and/or the point %d are not normalized, dot ptoduct is %f.\n",
124  getClassName ().c_str (), nn_indices[i_neigh], index, cos_between_normals);
125  throw PCLException ("Some normals are not normalized",
126  "spin_image.hpp", "computeSiForPoint");
127  }
128  cos_between_normals = std::max (-1.0, std::min (1.0, cos_between_normals));
129 
130  if (std::abs (cos_between_normals) < support_angle_cos_ ) // allow counter-directed normals
131  {
132  continue;
133  }
134 
135  if (cos_between_normals < 0.0)
136  {
137  cos_between_normals = -cos_between_normals; // the normal is not used explicitly from now
138  }
139  }
140 
141  // now compute the coordinate in cylindric coordinate system associated with the origin point
142  const Eigen::Vector3f direction (
143  (*surface_)[nn_indices[i_neigh]].getVector3fMap () - origin_point);
144  const double direction_norm = direction.norm ();
145  if (std::abs(direction_norm) < 10*std::numeric_limits<double>::epsilon ())
146  continue; // ignore the point itself; it does not contribute really
147  assert (direction_norm > 0.0);
148 
149  // the angle between the normal vector and the direction to the point
150  double cos_dir_axis = direction.dot(rotation_axis) / direction_norm;
151  if (std::abs(cos_dir_axis) > (1.0 + 10*std::numeric_limits<float>::epsilon())) // should be okay for numeric stability
152  {
153  PCL_ERROR ("[pcl::%s::computeSiForPoint] Rotation axis for the point %d are not normalized, dot ptoduct is %f.\n",
154  getClassName ().c_str (), index, cos_dir_axis);
155  throw PCLException ("Some rotation axis is not normalized",
156  "spin_image.hpp", "computeSiForPoint");
157  }
158  cos_dir_axis = std::max (-1.0, std::min (1.0, cos_dir_axis));
159 
160  // compute coordinates w.r.t. the reference frame
161  double beta = std::numeric_limits<double>::signaling_NaN ();
162  double alpha = std::numeric_limits<double>::signaling_NaN ();
163  if (is_radial_) // radial spin image structure
164  {
165  beta = asin (cos_dir_axis); // yes, arc sine! to get the angle against tangent, not normal!
166  alpha = direction_norm;
167  }
168  else // rectangular spin-image structure
169  {
170  beta = direction_norm * cos_dir_axis;
171  alpha = direction_norm * sqrt (1.0 - cos_dir_axis*cos_dir_axis);
172 
173  if (std::abs (beta) >= bin_size * image_width_ || alpha >= bin_size * image_width_)
174  {
175  continue; // outside the cylinder
176  }
177  }
178 
179  assert (alpha >= 0.0);
180  assert (alpha <= bin_size * image_width_ + 20 * std::numeric_limits<float>::epsilon () );
181 
182 
183  // bilinear interpolation
184  double beta_bin_size = is_radial_ ? (M_PI / 2 / image_width_) : bin_size;
185  int beta_bin = static_cast<int>(std::floor (beta / beta_bin_size)) + static_cast<int>(image_width_);
186  assert (0 <= beta_bin && beta_bin < m_matrix.cols ());
187  int alpha_bin = static_cast<int>(std::floor (alpha / bin_size));
188  assert (0 <= alpha_bin && alpha_bin < m_matrix.rows ());
189 
190  if (alpha_bin == static_cast<int> (image_width_)) // border points
191  {
192  alpha_bin--;
193  // HACK: to prevent a > 1
194  alpha = bin_size * (alpha_bin + 1) - std::numeric_limits<double>::epsilon ();
195  }
196  if (beta_bin == static_cast<int>(2*image_width_) ) // border points
197  {
198  beta_bin--;
199  // HACK: to prevent b > 1
200  beta = beta_bin_size * (beta_bin - static_cast<int>(image_width_) + 1) - std::numeric_limits<double>::epsilon ();
201  }
202 
203  double a = alpha/bin_size - static_cast<double>(alpha_bin);
204  double b = beta/beta_bin_size - static_cast<double>(beta_bin-static_cast<int>(image_width_));
205 
206  assert (0 <= a && a <= 1);
207  assert (0 <= b && b <= 1);
208 
209  m_matrix (alpha_bin, beta_bin) += (1-a) * (1-b);
210  m_matrix (alpha_bin+1, beta_bin) += a * (1-b);
211  m_matrix (alpha_bin, beta_bin+1) += (1-a) * b;
212  m_matrix (alpha_bin+1, beta_bin+1) += a * b;
213 
214  if (is_angular_)
215  {
216  m_averAngles (alpha_bin, beta_bin) += (1-a) * (1-b) * std::acos (cos_between_normals);
217  m_averAngles (alpha_bin+1, beta_bin) += a * (1-b) * std::acos (cos_between_normals);
218  m_averAngles (alpha_bin, beta_bin+1) += (1-a) * b * std::acos (cos_between_normals);
219  m_averAngles (alpha_bin+1, beta_bin+1) += a * b * std::acos (cos_between_normals);
220  }
221  }
222 
223  if (is_angular_)
224  {
225  // transform sum to average
226  m_matrix = m_averAngles / (m_matrix + std::numeric_limits<double>::epsilon ()); // +eps to avoid division by zero
227  }
228  else if (neighb_cnt > 1) // to avoid division by zero, also no need to divide by 1
229  {
230  // normalization
231  m_matrix /= m_matrix.sum();
232  }
233 
234  return m_matrix;
235 }
236 
237 
238 //////////////////////////////////////////////////////////////////////////////////////////////
239 template <typename PointInT, typename PointNT, typename PointOutT> bool
241 {
243  {
244  PCL_ERROR ("[pcl::%s::initCompute] Init failed.\n", getClassName ().c_str ());
245  return (false);
246  }
247 
248  // Check if input normals are set
249  if (!input_normals_)
250  {
251  PCL_ERROR ("[pcl::%s::initCompute] No input dataset containing normals was given!\n", getClassName ().c_str ());
253  return (false);
254  }
255 
256  // Check if the size of normals is the same as the size of the surface
257  if (input_normals_->size () != input_->size ())
258  {
259  PCL_ERROR ("[pcl::%s::initCompute] ", getClassName ().c_str ());
260  PCL_ERROR ("The number of points in the input dataset differs from ");
261  PCL_ERROR ("the number of points in the dataset containing the normals!\n");
263  return (false);
264  }
265 
266  // We need a positive definite search radius to continue
267  if (search_radius_ == 0)
268  {
269  PCL_ERROR ("[pcl::%s::initCompute] Need a search radius different than 0!\n", getClassName ().c_str ());
271  return (false);
272  }
273  if (k_ != 0)
274  {
275  PCL_ERROR ("[pcl::%s::initCompute] K-nearest neighbor search for spin images not implemented. Used a search radius instead!\n", getClassName ().c_str ());
277  return (false);
278  }
279  // If the surface won't be set, make fake surface and fake surface normals
280  // if we wouldn't do it here, the following method would alarm that no surface normals is given
281  if (!surface_)
282  {
283  surface_ = input_;
284  fake_surface_ = true;
285  }
286 
287  //if (fake_surface_ && !input_normals_)
288  // input_normals_ = normals_; // normals_ is set, as checked earlier
289 
290  assert(!(use_custom_axis_ && use_custom_axes_cloud_));
291 
292  if (!use_custom_axis_ && !use_custom_axes_cloud_ // use input normals as rotation axes
293  && !input_normals_)
294  {
295  PCL_ERROR ("[pcl::%s::initCompute] No normals for input cloud were given!\n", getClassName ().c_str ());
296  // Cleanup
298  return (false);
299  }
300 
301  if ((is_angular_ || support_angle_cos_ > 0.0) // support angle is not bogus NOTE this is for randomly-flipped normals
302  && !input_normals_)
303  {
304  PCL_ERROR ("[pcl::%s::initCompute] No normals for input cloud were given!\n", getClassName ().c_str ());
305  // Cleanup
307  return (false);
308  }
309 
310  if (use_custom_axes_cloud_
311  && rotation_axes_cloud_->size () == input_->size ())
312  {
313  PCL_ERROR ("[pcl::%s::initCompute] Rotation axis cloud have different size from input!\n", getClassName ().c_str ());
314  // Cleanup
316  return (false);
317  }
318 
319  return (true);
320 }
321 
322 
323 //////////////////////////////////////////////////////////////////////////////////////////////
324 template <typename PointInT, typename PointNT, typename PointOutT> void
326 {
327  for (std::size_t i_input = 0; i_input < indices_->size (); ++i_input)
328  {
329  Eigen::ArrayXXd res = computeSiForPoint (indices_->at (i_input));
330 
331  // Copy into the resultant cloud
332  for (Eigen::Index iRow = 0; iRow < res.rows () ; iRow++)
333  {
334  for (Eigen::Index iCol = 0; iCol < res.cols () ; iCol++)
335  {
336  output[i_input].histogram[ iRow*res.cols () + iCol ] = static_cast<float> (res (iRow, iCol));
337  }
338  }
339  }
340 }
341 
342 #define PCL_INSTANTIATE_SpinImageEstimation(T,NT,OutT) template class PCL_EXPORTS pcl::SpinImageEstimation<T,NT,OutT>;
343 
344 #endif // PCL_FEATURES_IMPL_SPIN_IMAGE_H_
345 
Feature represents the base feature class.
Definition: feature.h:107
std::string feature_name_
The feature name.
Definition: feature.h:220
virtual bool deinitCompute()
This method should get called after ending the actual computation.
Definition: feature.hpp:181
A base class for all pcl exceptions which inherits from std::runtime_error.
Definition: exceptions.h:64
Eigen::ArrayXXd computeSiForPoint(int index) const
Computes a spin-image for the point of the scan.
Definition: spin_image.hpp:70
void setImageWidth(unsigned int bin_count)
Sets spin-image resolution.
Definition: spin_image.h:134
SpinImageEstimation(unsigned int image_width=8, double support_angle_cos=0.0, unsigned int min_pts_neighb=0)
Constructs empty spin image estimator.
Definition: spin_image.hpp:52
bool initCompute() override
initializes computations specific to spin-image.
Definition: spin_image.hpp:240
void computeFeature(PointCloudOut &output) override
Estimate the Spin Image descriptors at a set of points given by setInputWithNormals() using the surfa...
Definition: spin_image.hpp:325
Defines all the PCL implemented PointT point type structures.
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133
#define M_PI
Definition: pcl_macros.h:201