sgf2.h
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00001 /*
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00037 
00038 #ifndef PCL_FEATURES_SGF2_H_
00039 #define PCL_FEATURES_SGF2_H_
00040 
00041 #include <pcl17/features/feature.h>
00042 #include <pcl17/features/normal_3d.h>
00043 #include <numeric>
00044 
00045 namespace pcl17 {
00046 const int SGF2_SIZE = 1;
00047 
00048 template<typename PointInT, typename PointOutT>
00049 class SGF2Estimation: public Feature<PointInT, PointOutT> {
00050 
00051 public:
00052 
00053         using Feature<PointInT, PointOutT>::feature_name_;
00054         using Feature<PointInT, PointOutT>::input_;
00055         using Feature<PointInT, PointOutT>::indices_;
00056         using Feature<PointInT, PointOutT>::search_parameter_;
00057         using Feature<PointInT, PointOutT>::k_;
00058 
00059         typedef typename Feature<PointInT, PointOutT>::PointCloudOut PointCloudOut;
00060         typedef typename Feature<PointInT, PointOutT>::PointCloudIn PointCloudIn;
00061 
00063         SGF2Estimation() {
00064                 feature_name_ = "SGF2Estimation";
00065                 k_ = 1;
00066         }
00067         ;
00068 
00070         void computeFeature(PointCloudOut &output) {
00071 
00072                 PointCloud<Normal>::Ptr normals(new PointCloud<Normal> ());
00073                 NormalEstimation<PointInT, Normal> n;
00074 
00075                 std::vector<int> nn_indices;
00076                 std::vector<float> nn_sqr_dists;
00077                 Eigen::Vector4f parameters;
00078                 Eigen::VectorXf vec(indices_->size());
00079 
00080                 for (size_t idx = 0; idx < indices_->size(); ++idx) {
00081                         float curvature;
00082                         this->searchForNeighbors((*indices_)[idx], search_parameter_,
00083                                         nn_indices, nn_sqr_dists);
00084                         n.computePointNormal(*input_, nn_indices, parameters, curvature);
00085                         vec[idx] = curvature;
00086                 }
00087 
00088                 output.points[0].histogram[0] = vec.mean();
00089 
00090         }
00092 
00093 
00094 private:
00095 
00099         void computeFeatureEigen(pcl17::PointCloud<Eigen::MatrixXf> &) {
00100         }
00101 };
00102 }
00103 
00104 #endif  //#ifndef PCL_FEATURES_SGF2_H_
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furniture_features
Author(s): Stefan
autogenerated on Thu May 23 2013 16:09:52