Point Cloud Library (PCL)  1.14.1-dev
linear_least_squares_normal.h
1 /*
2  * Software License Agreement (BSD License)
3  *
4  * Point Cloud Library (PCL) - www.pointclouds.org
5  * Copyright (c) 2010-2011, 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  */
38 
39 #pragma once
40 
41 #include <pcl/features/feature.h>
42 
43 namespace pcl
44 {
45  /** \brief Surface normal estimation on dense data using a least-squares estimation based on a first-order Taylor approximation.
46  * \author Stefan Holzer, Cedric Cagniart
47  */
48  template <typename PointInT, typename PointOutT>
49  class LinearLeastSquaresNormalEstimation : public Feature<PointInT, PointOutT>
50  {
51  public:
52  using Ptr = shared_ptr<LinearLeastSquaresNormalEstimation<PointInT, PointOutT> >;
53  using ConstPtr = shared_ptr<const LinearLeastSquaresNormalEstimation<PointInT, PointOutT> >;
60 
61  /** \brief Constructor */
63  {
64  feature_name_ = "LinearLeastSquaresNormalEstimation";
65  tree_.reset ();
66  k_ = 1;
67  }
68 
69  /** \brief Destructor */
71 
72  /** \brief Computes the normal at the specified position.
73  * \param[in] pos_x x position (pixel)
74  * \param[in] pos_y y position (pixel)
75  * \param[out] normal the output estimated normal
76  */
77  void
78  computePointNormal (const int pos_x, const int pos_y, PointOutT &normal);
79 
80  /** \brief Set the normal smoothing size
81  * \param[in] normal_smoothing_size factor which influences the size of the area used to smooth normals
82  * (depth dependent if useDepthDependentSmoothing is true)
83  */
84  void
85  setNormalSmoothingSize (float normal_smoothing_size)
86  {
87  normal_smoothing_size_ = normal_smoothing_size;
88  }
89 
90  /** \brief Set whether to use depth depending smoothing or not
91  * \param[in] use_depth_dependent_smoothing decides whether the smoothing is depth dependent
92  */
93  void
94  setDepthDependentSmoothing (bool use_depth_dependent_smoothing)
95  {
96  use_depth_dependent_smoothing_ = use_depth_dependent_smoothing;
97  }
98 
99  /** \brief The depth change threshold for computing object borders
100  * \param[in] max_depth_change_factor the depth change threshold for computing object borders based on
101  * depth changes
102  */
103  void
104  setMaxDepthChangeFactor (float max_depth_change_factor)
105  {
106  max_depth_change_factor_ = max_depth_change_factor;
107  }
108 
109  /** \brief Provide a pointer to the input dataset (overwrites the PCLBase::setInputCloud method)
110  * \param[in] cloud the const boost shared pointer to a PointCloud message
111  */
112  inline void
113  setInputCloud (const typename PointCloudIn::ConstPtr &cloud) override
114  {
115  input_ = cloud;
116  }
117 
118  protected:
119  /** \brief Computes the normal for the complete cloud.
120  * \param[out] output the resultant normals
121  */
122  void
123  computeFeature (PointCloudOut &output) override;
124 
125  private:
126 
127  /** the threshold used to detect depth discontinuities */
128  //float distance_threshold_;
129 
130  /** \brief Smooth data based on depth (true/false). */
131  bool use_depth_dependent_smoothing_{false};
132 
133  /** \brief Threshold for detecting depth discontinuities */
134  float max_depth_change_factor_{1.0f};
135 
136  /** \brief */
137  float normal_smoothing_size_{9.0f};
138  };
139 }
140 
141 #ifdef PCL_NO_PRECOMPILE
142 #include <pcl/features/impl/linear_least_squares_normal.hpp>
143 #endif
Feature represents the base feature class.
Definition: feature.h:107
int k_
The number of K nearest neighbors to use for each point.
Definition: feature.h:240
shared_ptr< Feature< PointInT, PointOutT > > Ptr
Definition: feature.h:114
std::string feature_name_
The feature name.
Definition: feature.h:220
shared_ptr< const Feature< PointInT, PointOutT > > ConstPtr
Definition: feature.h:115
KdTreePtr tree_
A pointer to the spatial search object.
Definition: feature.h:231
Surface normal estimation on dense data using a least-squares estimation based on a first-order Taylo...
void computePointNormal(const int pos_x, const int pos_y, PointOutT &normal)
Computes the normal at the specified position.
~LinearLeastSquaresNormalEstimation() override
Destructor.
typename Feature< PointInT, PointOutT >::PointCloudOut PointCloudOut
void setNormalSmoothingSize(float normal_smoothing_size)
Set the normal smoothing size.
void setInputCloud(const typename PointCloudIn::ConstPtr &cloud) override
Provide a pointer to the input dataset (overwrites the PCLBase::setInputCloud method)
void computeFeature(PointCloudOut &output) override
Computes the normal for the complete cloud.
void setMaxDepthChangeFactor(float max_depth_change_factor)
The depth change threshold for computing object borders.
void setDepthDependentSmoothing(bool use_depth_dependent_smoothing)
Set whether to use depth depending smoothing or not.
PointCloudConstPtr input_
The input point cloud dataset.
Definition: pcl_base.h:147
shared_ptr< const PointCloud< PointInT > > ConstPtr
Definition: point_cloud.h:414