sgf2.h

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#ifndef PCL_FEATURES_SGF2_H_
#define PCL_FEATURES_SGF2_H_

#include <pcl17/features/feature.h>
#include <pcl17/features/normal_3d.h>
#include <numeric>

namespace pcl17 {
const int SGF2_SIZE = 1;

template<typename PointInT, typename PointOutT>
class SGF2Estimation: public Feature<PointInT, PointOutT> {

public:

        using Feature<PointInT, PointOutT>::feature_name_;
        using Feature<PointInT, PointOutT>::input_;
        using Feature<PointInT, PointOutT>::indices_;
        using Feature<PointInT, PointOutT>::search_parameter_;
        using Feature<PointInT, PointOutT>::k_;

        typedef typename Feature<PointInT, PointOutT>::PointCloudOut PointCloudOut;
        typedef typename Feature<PointInT, PointOutT>::PointCloudIn PointCloudIn;

        SGF2Estimation() {
                feature_name_ = "SGF2Estimation";
                k_ = 1;
        }
        ;

        void computeFeature(PointCloudOut &output) {

                PointCloud<Normal>::Ptr normals(new PointCloud<Normal> ());
                NormalEstimation<PointInT, Normal> n;

                std::vector<int> nn_indices;
                std::vector<float> nn_sqr_dists;
                Eigen::Vector4f parameters;
                Eigen::VectorXf vec(indices_->size());

                for (size_t idx = 0; idx < indices_->size(); ++idx) {
                        float curvature;
                        this->searchForNeighbors((*indices_)[idx], search_parameter_,
                                        nn_indices, nn_sqr_dists);
                        n.computePointNormal(*input_, nn_indices, parameters, curvature);
                        vec[idx] = curvature;
                }

                output.points[0].histogram[0] = vec.mean();

        }


private:

        void computeFeatureEigen(pcl17::PointCloud<Eigen::MatrixXf> &) {
        }
};
}

#endif  //#ifndef PCL_FEATURES_SGF2_H_