Point Cloud Library (PCL) 1.12.0
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transformation_estimation_point_to_plane_lls_weighted.h
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39
40#pragma once
41
42#include <pcl/registration/transformation_estimation.h>
43#include <pcl/registration/warp_point_rigid.h>
44#include <pcl/cloud_iterator.h>
45
46namespace pcl {
47namespace registration {
48/** \brief @b TransformationEstimationPointToPlaneLLSWeighted implements a Linear Least
49 * Squares (LLS) approximation for minimizing the point-to-plane distance between two
50 * clouds of corresponding points with normals, with the possibility of assigning
51 * weights to the correspondences.
52 *
53 * For additional details, see
54 * "Linear Least-Squares Optimization for Point-to-Plane ICP Surface Registration",
55 * Kok-Lim Low, 2004
56 *
57 * \note The class is templated on the source and target point types as well as on the
58 * output scalar of the transformation matrix (i.e., float or double). Default: float.
59 * \author Alex Ichim
60 * \ingroup registration
61 */
62template <typename PointSource, typename PointTarget, typename Scalar = float>
64: public TransformationEstimation<PointSource, PointTarget, Scalar> {
65public:
67 PointTarget,
68 Scalar>>;
69 using ConstPtr =
70 shared_ptr<const TransformationEstimationPointToPlaneLLSWeighted<PointSource,
71 PointTarget,
72 Scalar>>;
73
74 using Matrix4 =
76
79
80 /** \brief Estimate a rigid rotation transformation between a source and a target
81 * point cloud using SVD. \param[in] cloud_src the source point cloud dataset
82 * \param[in] cloud_tgt the target point cloud dataset
83 * \param[out] transformation_matrix the resultant transformation matrix
84 */
85 inline void
89
90 /** \brief Estimate a rigid rotation transformation between a source and a target
91 * point cloud using SVD. \param[in] cloud_src the source point cloud dataset
92 * \param[in] indices_src the vector of indices describing the points of interest in
93 * \a cloud_src
94 * \param[in] cloud_tgt the target point cloud dataset
95 * \param[out] transformation_matrix the resultant transformation matrix
96 */
97 inline void
102
103 /** \brief Estimate a rigid rotation transformation between a source and a target
104 * point cloud using SVD. \param[in] cloud_src the source point cloud dataset
105 * \param[in] indices_src the vector of indices describing the points of interest in
106 * \a cloud_src
107 * \param[in] cloud_tgt the target point cloud dataset
108 * \param[in] indices_tgt the vector of indices describing the correspondences of the
109 * interest points from \a indices_src
110 * \param[out] transformation_matrix the resultant transformation matrix
111 */
112 inline void
118
119 /** \brief Estimate a rigid rotation transformation between a source and a target
120 * point cloud using SVD. \param[in] cloud_src the source point cloud dataset
121 * \param[in] cloud_tgt the target point cloud dataset
122 * \param[in] correspondences the vector of correspondences between source and target
123 * point cloud \param[out] transformation_matrix the resultant transformation matrix
124 */
125 inline void
128 const pcl::Correspondences& correspondences,
130
131 /** \brief Set the weights for the correspondences.
132 * \param[in] weights the weights for each correspondence
133 */
134 inline void
135 setCorrespondenceWeights(const std::vector<Scalar>& weights)
136 {
137 weights_ = weights;
138 }
139
140protected:
141 /** \brief Estimate a rigid rotation transformation between a source and a target
142 * \param[in] source_it an iterator over the source point cloud dataset
143 * \param[in] target_it an iterator over the target point cloud dataset
144 * \param weights_it
145 * \param[out] transformation_matrix the resultant transformation matrix
146 */
147 void
150 typename std::vector<Scalar>::const_iterator& weights_it,
152
153 /** \brief Construct a 4 by 4 transformation matrix from the provided rotation and
154 * translation. \param[in] alpha the rotation about the x-axis \param[in] beta the
155 * rotation about the y-axis \param[in] gamma the rotation about the z-axis \param[in]
156 * tx the x translation \param[in] ty the y translation \param[in] tz the z
157 * translation \param[out] transformation_matrix the resultant transformation matrix
158 */
159 inline void
161 const double& beta,
162 const double& gamma,
163 const double& tx,
164 const double& ty,
165 const double& tz,
167
168 std::vector<Scalar> weights_;
169};
170} // namespace registration
171} // namespace pcl
172
173#include <pcl/registration/impl/transformation_estimation_point_to_plane_lls_weighted.hpp>
Iterator class for point clouds with or without given indices.
TransformationEstimation represents the base class for methods for transformation estimation based on...
TransformationEstimationPointToPlaneLLSWeighted implements a Linear Least Squares (LLS) approximation...
void constructTransformationMatrix(const double &alpha, const double &beta, const double &gamma, const double &tx, const double &ty, const double &tz, Matrix4 &transformation_matrix) const
Construct a 4 by 4 transformation matrix from the provided rotation and translation.
void estimateRigidTransformation(const pcl::PointCloud< PointSource > &cloud_src, const pcl::PointCloud< PointTarget > &cloud_tgt, Matrix4 &transformation_matrix) const
Estimate a rigid rotation transformation between a source and a target point cloud using SVD.
typename TransformationEstimation< PointSource, PointTarget, Scalar >::Matrix4 Matrix4
void setCorrespondenceWeights(const std::vector< Scalar > &weights)
Set the weights for the correspondences.
std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > > Correspondences
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133