sac_model_normal_plane.h

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#pragma once
 
#include <pcl/memory.h>
#include <pcl/pcl_macros.h>
#include <pcl/sample_consensus/sac_model.h>
#include <pcl/sample_consensus/sac_model_plane.h>
#include <pcl/sample_consensus/model_types.h>
 
namespace pcl
{
  /** \brief SampleConsensusModelNormalPlane defines a model for 3D plane
    * segmentation using additional surface normal constraints. Basically this
    * means that checking for inliers will not only involve a "distance to
    * model" criterion, but also an additional "maximum angular deviation"
    * between the plane's normal and the inlier points normals.
    *
    * The model coefficients are defined as:
    *   - \b a : the X coordinate of the plane's normal (normalized)
    *   - \b b : the Y coordinate of the plane's normal (normalized)
    *   - \b c : the Z coordinate of the plane's normal (normalized)
    *   - \b d : the fourth <a href="http://mathworld.wolfram.com/HessianNormalForm.html">Hessian component</a> of the plane's equation
    *
    * To set the influence of the surface normals in the inlier estimation
    * process, set the normal weight (0.0-1.0), e.g.:
    * \code
    * SampleConsensusModelNormalPlane<pcl::PointXYZ, pcl::Normal> sac_model;
    * ...
    * sac_model.setNormalDistanceWeight (0.1);
    * ...
    * \endcode
    *
    * \author Radu B. Rusu and Jared Glover
    * \ingroup sample_consensus
    */
  template <typename PointT, typename PointNT>
  class SampleConsensusModelNormalPlane : public SampleConsensusModelPlane<PointT>, public SampleConsensusModelFromNormals<PointT, PointNT>
  {
    public:
      using SampleConsensusModel<PointT>::model_name_;
      using SampleConsensusModel<PointT>::input_;
      using SampleConsensusModel<PointT>::indices_;
      using SampleConsensusModelFromNormals<PointT, PointNT>::normals_;
      using SampleConsensusModelFromNormals<PointT, PointNT>::normal_distance_weight_;
      using SampleConsensusModel<PointT>::error_sqr_dists_;
      using SampleConsensusModel<PointT>::isModelValid;
 
      using PointCloud = typename SampleConsensusModel<PointT>::PointCloud;
      using PointCloudPtr = typename SampleConsensusModel<PointT>::PointCloudPtr;
      using PointCloudConstPtr = typename SampleConsensusModel<PointT>::PointCloudConstPtr;
 
      using PointCloudNPtr = typename SampleConsensusModelFromNormals<PointT, PointNT>::PointCloudNPtr;
      using PointCloudNConstPtr = typename SampleConsensusModelFromNormals<PointT, PointNT>::PointCloudNConstPtr;
 
      using Ptr = shared_ptr<SampleConsensusModelNormalPlane<PointT, PointNT> >;
      using ConstPtr = shared_ptr<const SampleConsensusModelNormalPlane<PointT, PointNT>>;
 
      /** \brief Constructor for base SampleConsensusModelNormalPlane.
        * \param[in] cloud the input point cloud dataset
        * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
        */
      SampleConsensusModelNormalPlane (const PointCloudConstPtr &cloud, 
                                       bool random = false) 
        : SampleConsensusModelPlane<PointT> (cloud, random)
        , SampleConsensusModelFromNormals<PointT, PointNT> ()
      {
        model_name_ = "SampleConsensusModelNormalPlane";
        sample_size_ = 3;
        model_size_ = 4;
      }
 
      /** \brief Constructor for base SampleConsensusModelNormalPlane.
        * \param[in] cloud the input point cloud dataset
        * \param[in] indices a vector of point indices to be used from \a cloud
        * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
        */
      SampleConsensusModelNormalPlane (const PointCloudConstPtr &cloud, 
                                       const Indices &indices,
                                       bool random = false) 
        : SampleConsensusModelPlane<PointT> (cloud, indices, random)
        , SampleConsensusModelFromNormals<PointT, PointNT> ()
      {
        model_name_ = "SampleConsensusModelNormalPlane";
        sample_size_ = 3;
        model_size_ = 4;
      }
      
      /** \brief Empty destructor */
      ~SampleConsensusModelNormalPlane () override = default;
 
      /** \brief Select all the points which respect the given model coefficients as inliers.
        * \param[in] model_coefficients the coefficients of a plane model that we need to compute distances to
        * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
        * \param[out] inliers the resultant model inliers
        */
      void 
      selectWithinDistance (const Eigen::VectorXf &model_coefficients, 
                            const double threshold, 
                            Indices &inliers) override;
 
      /** \brief Count all the points which respect the given model coefficients as inliers. 
        * 
        * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
        * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
        * \return the resultant number of inliers
        */
      std::size_t
      countWithinDistance (const Eigen::VectorXf &model_coefficients,
                           const double threshold) const override;
 
      /** \brief Compute all distances from the cloud data to a given plane model.
        * \param[in] model_coefficients the coefficients of a plane model that we need to compute distances to
        * \param[out] distances the resultant estimated distances
        */
      void
      getDistancesToModel (const Eigen::VectorXf &model_coefficients,
                           std::vector<double> &distances) const override;
 
      /** \brief Return a unique id for this model (SACMODEL_NORMAL_PLANE). */
      inline pcl::SacModel 
      getModelType () const override { return (SACMODEL_NORMAL_PLANE); }
 
      PCL_MAKE_ALIGNED_OPERATOR_NEW
 
    protected:
      using SampleConsensusModel<PointT>::sample_size_;
      using SampleConsensusModel<PointT>::model_size_;
 
      /** This implementation uses no SIMD instructions. It is not intended for normal use.
        * See countWithinDistance which automatically uses the fastest implementation.
        */
      std::size_t
      countWithinDistanceStandard (const Eigen::VectorXf &model_coefficients,
                                   const double threshold,
                                   std::size_t i = 0) const;
 
#if defined (__SSE__) && defined (__SSE2__) && defined (__SSE4_1__)
      /** This implementation uses SSE, SSE2, and SSE4.1 instructions. It is not intended for normal use.
        * See countWithinDistance which automatically uses the fastest implementation.
        */
      std::size_t
      countWithinDistanceSSE (const Eigen::VectorXf &model_coefficients,
                              const double threshold,
                              std::size_t i = 0) const;
#endif
 
#if defined (__AVX__) && defined (__AVX2__)
      /** This implementation uses AVX and AVX2 instructions. It is not intended for normal use.
        * See countWithinDistance which automatically uses the fastest implementation.
        */
      std::size_t
      countWithinDistanceAVX (const Eigen::VectorXf &model_coefficients,
                              const double threshold,
                              std::size_t i = 0) const;
#endif
  };
}
 
#ifdef PCL_NO_PRECOMPILE
#include <pcl/sample_consensus/impl/sac_model_normal_plane.hpp>
#endif