Point Cloud Library (PCL)  1.11.1-dev
keypoint.hpp
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37 
38 
39 #ifndef PCL_KEYPOINT_IMPL_H_
40 #define PCL_KEYPOINT_IMPL_H_
41 
42 #include <pcl/console/print.h> // for PCL_ERROR
43 
44 #include <pcl/search/organized.h> // for OrganizedNeighbor
45 #include <pcl/search/kdtree.h> // for KdTree
46 
47 namespace pcl
48 {
49 
50 template <typename PointInT, typename PointOutT> bool
52 {
54  return (false);
55 
56  // Initialize the spatial locator
57  if (!tree_)
58  {
59  if (input_->isOrganized ())
60  tree_.reset (new pcl::search::OrganizedNeighbor<PointInT> ());
61  else
62  tree_.reset (new pcl::search::KdTree<PointInT> (false));
63  }
64 
65  // If no search surface has been defined, use the input dataset as the search surface itself
66  if (!surface_)
67  surface_ = input_;
68 
69  // Send the surface dataset to the spatial locator
70  tree_->setInputCloud (surface_);
71 
72  // Do a fast check to see if the search parameters are well defined
73  if (search_radius_ != 0.0)
74  {
75  if (k_ != 0)
76  {
77  PCL_ERROR ("[pcl::%s::initCompute] Both radius (%f) and K (%d) defined! Set one of them to zero first and then re-run compute ().\n", getClassName ().c_str (), search_radius_, k_);
78  return (false);
79  }
80 
81  // Use the radiusSearch () function
82  search_parameter_ = search_radius_;
83  if (surface_ == input_) // if the two surfaces are the same
84  {
85  // Declare the search locator definition
86  search_method_ = [this] (int index, double radius, std::vector<int> &k_indices, std::vector<float> &k_distances)
87  {
88  return tree_->radiusSearch (index, radius, k_indices, k_distances, 0);
89  };
90  }
91  else
92  {
93  // Declare the search locator definition
94  search_method_surface_ = [this] (const PointCloudIn &cloud, int index, double radius, std::vector<int> &k_indices, std::vector<float> &k_distances)
95  {
96  return tree_->radiusSearch (cloud, index, radius, k_indices, k_distances, 0);
97  };
98  }
99  }
100  else
101  {
102  if (k_ != 0) // Use the nearestKSearch () function
103  {
104  search_parameter_ = k_;
105  if (surface_ == input_) // if the two surfaces are the same
106  {
107  // Declare the search locator definition
108  search_method_ = [this] (int index, int k, std::vector<int> &k_indices, std::vector<float> &k_distances)
109  {
110  return tree_->nearestKSearch (index, k, k_indices, k_distances);
111  };
112  }
113  else
114  {
115  // Declare the search locator definition
116  search_method_surface_ = [this] (const PointCloudIn &cloud, int index, int k, std::vector<int> &k_indices, std::vector<float> &k_distances)
117  {
118  return tree_->nearestKSearch (cloud, index, k, k_indices, k_distances);
119  };
120  }
121  }
122  else
123  {
124  PCL_ERROR ("[pcl::%s::initCompute] Neither radius nor K defined! Set one of them to a positive number first and then re-run compute ().\n", getClassName ().c_str ());
125  return (false);
126  }
127  }
128 
129  keypoints_indices_.reset (new pcl::PointIndices);
130  keypoints_indices_->indices.reserve (input_->size ());
131 
132  return (true);
133 }
134 
135 
136 template <typename PointInT, typename PointOutT> inline void
138 {
139  if (!initCompute ())
140  {
141  PCL_ERROR ("[pcl::%s::compute] initCompute failed!\n", getClassName ().c_str ());
142  return;
143  }
144 
145  // Perform the actual computation
146  detectKeypoints (output);
147 
148  deinitCompute ();
149 
150  // Reset the surface
151  if (input_ == surface_)
152  surface_.reset ();
153 }
154 
155 } // namespace pcl
156 
157 #endif //#ifndef PCL_KEYPOINT_IMPL_H_
158 
pcl::Keypoint::initCompute
virtual bool initCompute()
Definition: keypoint.hpp:51
pcl
Definition: convolution.h:46
pcl::PCLBase
PCL base class.
Definition: pcl_base.h:69
pcl::PointCloud< PointInT >
pcl::search::KdTree
search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search function...
Definition: kdtree.h:61
pcl::PointIndices
Definition: PointIndices.h:11
pcl::search::OrganizedNeighbor
OrganizedNeighbor is a class for optimized nearest neigbhor search in organized point clouds.
Definition: organized.h:62
pcl::Keypoint
Keypoint represents the base class for key points.
Definition: keypoint.h:49