Point Cloud Library (PCL)  1.3.1
normal_3d.hpp
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00001 /*
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00034  * $Id: normal_3d.hpp 2395 2011-09-06 16:20:51Z rusu $
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00037 
00038 #ifndef PCL_FEATURES_IMPL_NORMAL_3D_H_
00039 #define PCL_FEATURES_IMPL_NORMAL_3D_H_
00040 
00041 #include "pcl/features/normal_3d.h"
00042 
00044 template <typename PointInT, typename PointOutT> void
00045 pcl::NormalEstimation<PointInT, PointOutT>::computeFeature (PointCloudOut &output)
00046 {
00047   // Allocate enough space to hold the results
00048   // \note This resize is irrelevant for a radiusSearch ().
00049   std::vector<int> nn_indices (k_);
00050   std::vector<float> nn_dists (k_);
00051 
00052   // Iterating over the entire index vector
00053   for (size_t idx = 0; idx < indices_->size (); ++idx)
00054   {
00055     if (!this->searchForNeighbors ((*indices_)[idx], search_parameter_, nn_indices, nn_dists))
00056     {
00057       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 ();
00058       continue;
00059     }
00060 
00061     computePointNormal (*surface_, nn_indices,
00062                         output.points[idx].normal[0], output.points[idx].normal[1], output.points[idx].normal[2], output.points[idx].curvature);
00063 
00064     flipNormalTowardsViewpoint (input_->points[(*indices_)[idx]], vpx_, vpy_, vpz_,
00065                                 output.points[idx].normal[0], output.points[idx].normal[1], output.points[idx].normal[2]);
00066 
00067   }
00068 }
00069 
00070 #define PCL_INSTANTIATE_NormalEstimation(T,NT) template class PCL_EXPORTS pcl::NormalEstimation<T,NT>;
00071 
00072 #endif    // PCL_FEATURES_IMPL_NORMAL_3D_H_ 
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