Point Cloud Library (PCL)  1.11.1-dev
projection_matrix.hpp
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37 
38 #pragma once
39 
40 #include <pcl/common/projection_matrix.h>
41 #include <pcl/console/print.h> // for PCL_ERROR
42 #include <pcl/cloud_iterator.h>
43 
44 #include <Eigen/Eigenvalues> // for SelfAdjointEigenSolver
45 
46 namespace pcl
47 {
48 
49 namespace common
50 {
51 
52 namespace internal
53 {
54 
55 template <typename MatrixT> void
56 makeSymmetric (MatrixT& matrix, bool use_upper_triangular = true)
57 {
58  if (use_upper_triangular && (MatrixT::Flags & Eigen::RowMajorBit))
59  {
60  matrix.coeffRef (4) = matrix.coeff (1);
61  matrix.coeffRef (8) = matrix.coeff (2);
62  matrix.coeffRef (9) = matrix.coeff (6);
63  matrix.coeffRef (12) = matrix.coeff (3);
64  matrix.coeffRef (13) = matrix.coeff (7);
65  matrix.coeffRef (14) = matrix.coeff (11);
66  }
67  else
68  {
69  matrix.coeffRef (1) = matrix.coeff (4);
70  matrix.coeffRef (2) = matrix.coeff (8);
71  matrix.coeffRef (6) = matrix.coeff (9);
72  matrix.coeffRef (3) = matrix.coeff (12);
73  matrix.coeffRef (7) = matrix.coeff (13);
74  matrix.coeffRef (11) = matrix.coeff (14);
75  }
76 }
77 
78 } // namespace internal
79 } // namespace common
80 
81 
82 template <typename PointT> double
84  typename pcl::PointCloud<PointT>::ConstPtr cloud,
85  Eigen::Matrix<float, 3, 4, Eigen::RowMajor>& projection_matrix,
86  const Indices& indices)
87 {
88  // internally we calculate with double but store the result into float matrices.
89  using Scalar = double;
90  projection_matrix.setZero ();
91  if (cloud->height == 1 || cloud->width == 1)
92  {
93  PCL_ERROR ("[pcl::estimateProjectionMatrix] Input dataset is not organized!\n");
94  return (-1.0);
95  }
96 
97  Eigen::Matrix<Scalar, 4, 4, Eigen::RowMajor> A = Eigen::Matrix<Scalar, 4, 4, Eigen::RowMajor>::Zero ();
98  Eigen::Matrix<Scalar, 4, 4, Eigen::RowMajor> B = Eigen::Matrix<Scalar, 4, 4, Eigen::RowMajor>::Zero ();
99  Eigen::Matrix<Scalar, 4, 4, Eigen::RowMajor> C = Eigen::Matrix<Scalar, 4, 4, Eigen::RowMajor>::Zero ();
100  Eigen::Matrix<Scalar, 4, 4, Eigen::RowMajor> D = Eigen::Matrix<Scalar, 4, 4, Eigen::RowMajor>::Zero ();
101 
102  pcl::ConstCloudIterator <PointT> pointIt (*cloud, indices);
103 
104  while (pointIt)
105  {
106  unsigned yIdx = pointIt.getCurrentPointIndex () / cloud->width;
107  unsigned xIdx = pointIt.getCurrentPointIndex () % cloud->width;
108 
109  const PointT& point = *pointIt;
110  if (std::isfinite (point.x))
111  {
112  Scalar xx = point.x * point.x;
113  Scalar xy = point.x * point.y;
114  Scalar xz = point.x * point.z;
115  Scalar yy = point.y * point.y;
116  Scalar yz = point.y * point.z;
117  Scalar zz = point.z * point.z;
118  Scalar xx_yy = xIdx * xIdx + yIdx * yIdx;
119 
120  A.coeffRef (0) += xx;
121  A.coeffRef (1) += xy;
122  A.coeffRef (2) += xz;
123  A.coeffRef (3) += point.x;
124 
125  A.coeffRef (5) += yy;
126  A.coeffRef (6) += yz;
127  A.coeffRef (7) += point.y;
128 
129  A.coeffRef (10) += zz;
130  A.coeffRef (11) += point.z;
131  A.coeffRef (15) += 1.0;
132 
133  B.coeffRef (0) -= xx * xIdx;
134  B.coeffRef (1) -= xy * xIdx;
135  B.coeffRef (2) -= xz * xIdx;
136  B.coeffRef (3) -= point.x * static_cast<double>(xIdx);
137 
138  B.coeffRef (5) -= yy * xIdx;
139  B.coeffRef (6) -= yz * xIdx;
140  B.coeffRef (7) -= point.y * static_cast<double>(xIdx);
141 
142  B.coeffRef (10) -= zz * xIdx;
143  B.coeffRef (11) -= point.z * static_cast<double>(xIdx);
144 
145  B.coeffRef (15) -= xIdx;
146 
147  C.coeffRef (0) -= xx * yIdx;
148  C.coeffRef (1) -= xy * yIdx;
149  C.coeffRef (2) -= xz * yIdx;
150  C.coeffRef (3) -= point.x * static_cast<double>(yIdx);
151 
152  C.coeffRef (5) -= yy * yIdx;
153  C.coeffRef (6) -= yz * yIdx;
154  C.coeffRef (7) -= point.y * static_cast<double>(yIdx);
155 
156  C.coeffRef (10) -= zz * yIdx;
157  C.coeffRef (11) -= point.z * static_cast<double>(yIdx);
158 
159  C.coeffRef (15) -= yIdx;
160 
161  D.coeffRef (0) += xx * xx_yy;
162  D.coeffRef (1) += xy * xx_yy;
163  D.coeffRef (2) += xz * xx_yy;
164  D.coeffRef (3) += point.x * xx_yy;
165 
166  D.coeffRef (5) += yy * xx_yy;
167  D.coeffRef (6) += yz * xx_yy;
168  D.coeffRef (7) += point.y * xx_yy;
169 
170  D.coeffRef (10) += zz * xx_yy;
171  D.coeffRef (11) += point.z * xx_yy;
172 
173  D.coeffRef (15) += xx_yy;
174  }
175 
176  ++pointIt;
177  } // while
178 
183 
184  Eigen::Matrix<Scalar, 12, 12, Eigen::RowMajor> X = Eigen::Matrix<Scalar, 12, 12, Eigen::RowMajor>::Zero ();
185  X.topLeftCorner<4,4> ().matrix () = A;
186  X.block<4,4> (0, 8).matrix () = B;
187  X.block<4,4> (8, 0).matrix () = B;
188  X.block<4,4> (4, 4).matrix () = A;
189  X.block<4,4> (4, 8).matrix () = C;
190  X.block<4,4> (8, 4).matrix () = C;
191  X.block<4,4> (8, 8).matrix () = D;
192 
193  Eigen::SelfAdjointEigenSolver<Eigen::Matrix<Scalar, 12, 12, Eigen::RowMajor> > ei_symm (X);
194  Eigen::Matrix<Scalar, 12, 12, Eigen::RowMajor> eigen_vectors = ei_symm.eigenvectors ();
195 
196  // check whether the residual MSE is low. If its high, the cloud was not captured from a projective device.
197  Eigen::Matrix<Scalar, 1, 1> residual_sqr = eigen_vectors.col (0).transpose () * X * eigen_vectors.col (0);
198 
199  double residual = residual_sqr.coeff (0);
200 
201  projection_matrix.coeffRef (0) = static_cast <float> (eigen_vectors.coeff (0));
202  projection_matrix.coeffRef (1) = static_cast <float> (eigen_vectors.coeff (12));
203  projection_matrix.coeffRef (2) = static_cast <float> (eigen_vectors.coeff (24));
204  projection_matrix.coeffRef (3) = static_cast <float> (eigen_vectors.coeff (36));
205  projection_matrix.coeffRef (4) = static_cast <float> (eigen_vectors.coeff (48));
206  projection_matrix.coeffRef (5) = static_cast <float> (eigen_vectors.coeff (60));
207  projection_matrix.coeffRef (6) = static_cast <float> (eigen_vectors.coeff (72));
208  projection_matrix.coeffRef (7) = static_cast <float> (eigen_vectors.coeff (84));
209  projection_matrix.coeffRef (8) = static_cast <float> (eigen_vectors.coeff (96));
210  projection_matrix.coeffRef (9) = static_cast <float> (eigen_vectors.coeff (108));
211  projection_matrix.coeffRef (10) = static_cast <float> (eigen_vectors.coeff (120));
212  projection_matrix.coeffRef (11) = static_cast <float> (eigen_vectors.coeff (132));
213 
214  if (projection_matrix.coeff (0) < 0)
215  projection_matrix *= -1.0;
216 
217  return (residual);
218 }
219 
220 } // namespace pcl
221 
pcl
Definition: convolution.h:46
pcl::PointCloud::height
std::uint32_t height
The point cloud height (if organized as an image-structure).
Definition: point_cloud.h:415
pcl::ConstCloudIterator::getCurrentPointIndex
unsigned getCurrentPointIndex() const
Definition: cloud_iterator.hpp:523
pcl::estimateProjectionMatrix
double estimateProjectionMatrix(typename pcl::PointCloud< PointT >::ConstPtr cloud, Eigen::Matrix< float, 3, 4, Eigen::RowMajor > &projection_matrix, const Indices &indices)
Estimates the projection matrix P = K * (R|-R*t) from organized point clouds, with K = [[fx,...
Definition: projection_matrix.hpp:83
pcl::PointXYZRGB
A point structure representing Euclidean xyz coordinates, and the RGB color.
Definition: point_types.hpp:628
pcl::PointCloud::width
std::uint32_t width
The point cloud width (if organized as an image-structure).
Definition: point_cloud.h:413
pcl::Indices
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:141
pcl::common::internal::makeSymmetric
void makeSymmetric(MatrixT &matrix, bool use_upper_triangular=true)
Definition: projection_matrix.hpp:56
pcl::B
@ B
Definition: norms.h:54
pcl::PointCloud::ConstPtr
shared_ptr< const PointCloud< PointT > > ConstPtr
Definition: point_cloud.h:429
pcl::ConstCloudIterator
Iterator class for point clouds with or without given indices.
Definition: cloud_iterator.h:120