/features/include/pcl/features/ppf.h

/*
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 *
 *  Point Cloud Library (PCL) - www.pointclouds.org
 *  Copyright (c) 2011, Alexandru-Eugen Ichim
 *                      Willow Garage, Inc
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#ifndef PCL_PPF_H_
#define PCL_PPF_H_

#include <pcl/features/feature.h>
#include <boost/unordered_map.hpp>

namespace pcl
{
  /** \brief
    * \param[in] p1 
    * \param[in] n1
    * \param[in] p2 
    * \param[in] n2
    * \param[out] f1
    * \param[out] f2
    * \param[out] f3
    * \param[out] f4
    */
  PCL_EXPORTS bool
  computePPFPairFeature (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1,
                         const Eigen::Vector4f &p2, const Eigen::Vector4f &n2,
                         float &f1, float &f2, float &f3, float &f4);


  /** \brief Class that calculates the "surflet" features for each pair in the given
    * pointcloud. Please refer to the following publication for more details:
    *    B. Drost, M. Ulrich, N. Navab, S. Ilic
    *    Model Globally, Match Locally: Efficient and Robust 3D Object Recognition
    *    2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
    *    13-18 June 2010, San Francisco, CA
    *
    * PointOutT is meant to be pcl::PPFSignature - contains the 4 values of the Surflet
    * feature and in addition, alpha_m for the respective pair - optimization proposed by
    * the authors (see above)
    *
    * \author Alexandru-Eugen Ichim
    */
  template <typename PointInT, typename PointNT, typename PointOutT>
  class PPFEstimation : public FeatureFromNormals<PointInT, PointNT, PointOutT>
  {
    public:
      using PCLBase<PointInT>::indices_;
      using Feature<PointInT, PointOutT>::input_;
      using Feature<PointInT, PointOutT>::feature_name_;
      using Feature<PointInT, PointOutT>::getClassName;
      using FeatureFromNormals<PointInT, PointNT, PointOutT>::normals_;

      typedef pcl::PointCloud<PointOutT> PointCloudOut;

      /** \brief Empty Constructor. */
      PPFEstimation ();


    private:
      /** \brief The method called for actually doing the computations
        * \param[out] output the resulting point cloud (which should be of type pcl::PPFSignature);
        * its size is the size of the input cloud, squared (i.e., one point for each pair in
        * the input cloud);
        */
      void
      computeFeature (PointCloudOut &output);

      /** \brief Make the computeFeature (&Eigen::MatrixXf); inaccessible from outside the class
        * \param[out] output the output point cloud 
        */
      void 
      computeFeatureEigen (pcl::PointCloud<Eigen::MatrixXf> &) {}
  };

  /** \brief Class that calculates the "surflet" features for each pair in the given
    * pointcloud. Please refer to the following publication for more details:
    *    B. Drost, M. Ulrich, N. Navab, S. Ilic
    *    Model Globally, Match Locally: Efficient and Robust 3D Object Recognition
    *    2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
    *    13-18 June 2010, San Francisco, CA
    *
    * PointOutT is meant to be pcl::PPFSignature - contains the 4 values of the Surflet
    * feature and in addition, alpha_m for the respective pair - optimization proposed by
    * the authors (see above)
    *
    * \author Alexandru-Eugen Ichim
    */
  template <typename PointInT, typename PointNT>
  class PPFEstimation<PointInT, PointNT, Eigen::MatrixXf> : public PPFEstimation<PointInT, PointNT, pcl::PPFSignature>
  {
    public:
      using PPFEstimation<PointInT, PointNT, pcl::PPFSignature>::getClassName;
      using PPFEstimation<PointInT, PointNT, pcl::PPFSignature>::input_;
      using PPFEstimation<PointInT, PointNT, pcl::PPFSignature>::normals_;
      using PPFEstimation<PointInT, PointNT, pcl::PPFSignature>::indices_;

    private:
      /** \brief The method called for actually doing the computations
        * \param[out] output the resulting point cloud
        * its size is the size of the input cloud, squared (i.e., one point for each pair in
        * the input cloud);
        */
      void
      computeFeatureEigen (pcl::PointCloud<Eigen::MatrixXf> &output);

      /** \brief Make the compute (&PointCloudOut); inaccessible from outside the class
        * \param[out] output the output point cloud 
        */
      void 
      compute (pcl::PointCloud<pcl::Normal> &) {}
  };
}

#endif // PCL_PPF_H_