Point Cloud Library (PCL)  1.8.1-dev
normal_3d.hpp
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40 
41 #ifndef PCL_FEATURES_IMPL_NORMAL_3D_H_
42 #define PCL_FEATURES_IMPL_NORMAL_3D_H_
43 
44 #include <pcl/features/normal_3d.h>
45 
46 ///////////////////////////////////////////////////////////////////////////////////////////
47 template <typename PointInT, typename PointOutT> void
49 {
50  // Allocate enough space to hold the results
51  // \note This resize is irrelevant for a radiusSearch ().
52  std::vector<int> nn_indices (k_);
53  std::vector<float> nn_dists (k_);
54 
55  output.is_dense = true;
56  // Save a few cycles by not checking every point for NaN/Inf values if the cloud is set to dense
57  if (input_->is_dense)
58  {
59  // Iterating over the entire index vector
60  for (size_t idx = 0; idx < indices_->size (); ++idx)
61  {
62  if (this->searchForNeighbors ((*indices_)[idx], search_parameter_, nn_indices, nn_dists) == 0 ||
63  !computePointNormal (*surface_, nn_indices, output.points[idx].normal[0], output.points[idx].normal[1], output.points[idx].normal[2], output.points[idx].curvature))
64  {
65  output.points[idx].normal[0] = output.points[idx].normal[1] = output.points[idx].normal[2] = output.points[idx].curvature = std::numeric_limits<float>::quiet_NaN ();
66 
67  output.is_dense = false;
68  continue;
69  }
70 
71  flipNormalTowardsViewpoint (input_->points[(*indices_)[idx]], vpx_, vpy_, vpz_,
72  output.points[idx].normal[0], output.points[idx].normal[1], output.points[idx].normal[2]);
73 
74  }
75  }
76  else
77  {
78  // Iterating over the entire index vector
79  for (size_t idx = 0; idx < indices_->size (); ++idx)
80  {
81  if (!isFinite ((*input_)[(*indices_)[idx]]) ||
82  this->searchForNeighbors ((*indices_)[idx], search_parameter_, nn_indices, nn_dists) == 0 ||
83  !computePointNormal (*surface_, nn_indices, output.points[idx].normal[0], output.points[idx].normal[1], output.points[idx].normal[2], output.points[idx].curvature))
84  {
85  output.points[idx].normal[0] = output.points[idx].normal[1] = output.points[idx].normal[2] = output.points[idx].curvature = std::numeric_limits<float>::quiet_NaN ();
86 
87  output.is_dense = false;
88  continue;
89  }
90 
91  flipNormalTowardsViewpoint (input_->points[(*indices_)[idx]], vpx_, vpy_, vpz_,
92  output.points[idx].normal[0], output.points[idx].normal[1], output.points[idx].normal[2]);
93 
94  }
95  }
96 }
97 
98 #define PCL_INSTANTIATE_NormalEstimation(T,NT) template class PCL_EXPORTS pcl::NormalEstimation<T,NT>;
99 
100 #endif // PCL_FEATURES_IMPL_NORMAL_3D_H_
bool isFinite(const PointT &pt)
Tests if the 3D components of a point are all finite param[in] pt point to be tested return true if f...
Definition: point_tests.h:54
bool computePointNormal(const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f &plane_parameters, float &curvature)
Compute the Least-Squares plane fit for a given set of points, and return the estimated plane paramet...
Definition: normal_3d.h:60
std::vector< PointT, Eigen::aligned_allocator< PointT > > points
The point data.
Definition: point_cloud.h:410
void flipNormalTowardsViewpoint(const PointT &point, float vp_x, float vp_y, float vp_z, Eigen::Matrix< Scalar, 4, 1 > &normal)
Flip (in place) the estimated normal of a point towards a given viewpoint.
Definition: normal_3d.h:121
PointCloud represents the base class in PCL for storing collections of 3D points. ...
void computeFeature(PointCloudOut &output)
Estimate normals for all points given in <setInputCloud (), setIndices ()> using the surface in setSe...
Definition: normal_3d.hpp:48
bool is_dense
True if no points are invalid (e.g., have NaN or Inf values).
Definition: point_cloud.h:418