integral_image_normal.h

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#ifndef PCL_INTEGRALIMAGE_BASED_NORMAL_ESTIMATOR_H_
#define PCL_INTEGRALIMAGE_BASED_NORMAL_ESTIMATOR_H_

#include <pcl/point_cloud.h>
#include <pcl/point_types.h>
#include <pcl/features/feature.h>
#include <pcl/features/integral_image2D.h>

#if defined BUILD_Maintainer && defined __GNUC__ && __GNUC__ == 4 && __GNUC_MINOR__ > 3
#pragma GCC diagnostic ignored "-Weffc++"
#endif
namespace pcl
{
  template <typename PointInT, typename PointOutT>
  class IntegralImageNormalEstimation: public Feature<PointInT, PointOutT>
  {
    using Feature<PointInT, PointOutT>::input_;
    using Feature<PointInT, PointOutT>::feature_name_;
    using Feature<PointInT, PointOutT>::tree_;
    using Feature<PointInT, PointOutT>::k_;

    public:
      typedef boost::shared_ptr<IntegralImageNormalEstimation<PointInT, PointOutT> > Ptr;
      typedef boost::shared_ptr<const IntegralImageNormalEstimation<PointInT, PointOutT> > ConstPtr;

        enum BorderPolicy
        {
          BORDER_POLICY_IGNORE,
          BORDER_POLICY_MIRROR
        };

      enum NormalEstimationMethod
      {
        COVARIANCE_MATRIX,
        AVERAGE_3D_GRADIENT,
        AVERAGE_DEPTH_CHANGE,
        SIMPLE_3D_GRADIENT
      };

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

      IntegralImageNormalEstimation ()
        : normal_estimation_method_(AVERAGE_3D_GRADIENT)
        , border_policy_ (BORDER_POLICY_IGNORE)
        , rect_width_ (0), rect_width_2_ (0), rect_width_4_ (0)
        , rect_height_ (0), rect_height_2_ (0), rect_height_4_ (0)
        , distance_threshold_ (0)
        , integral_image_DX_ (false)
        , integral_image_DY_ (false)
        , integral_image_depth_ (false)
        , integral_image_XYZ_ (true)
        , diff_x_ (NULL)
        , diff_y_ (NULL)
        , depth_data_ (NULL)
        , distance_map_ (NULL)
        , use_depth_dependent_smoothing_ (false)
        , max_depth_change_factor_ (20.0f*0.001f)
        , normal_smoothing_size_ (10.0f)
        , init_covariance_matrix_ (false)
        , init_average_3d_gradient_ (false)
        , init_simple_3d_gradient_ (false)
        , init_depth_change_ (false)
        , vpx_ (0.0f)
        , vpy_ (0.0f)
        , vpz_ (0.0f)
        , use_sensor_origin_ (true)
      {
        feature_name_ = "IntegralImagesNormalEstimation";
        tree_.reset ();
        k_ = 1;
      }

      virtual ~IntegralImageNormalEstimation ();

      void
      setRectSize (const int width, const int height);

      void
      setBorderPolicy (const BorderPolicy border_policy)
      {
        border_policy_ = border_policy;
      }

      void
      computePointNormal (const int pos_x, const int pos_y, const unsigned point_index, PointOutT &normal);

      void
      computePointNormalMirror (const int pos_x, const int pos_y, const unsigned point_index, PointOutT &normal);

      void
      setMaxDepthChangeFactor (float max_depth_change_factor)
      {
        max_depth_change_factor_ = max_depth_change_factor;
      }

      void
      setNormalSmoothingSize (float normal_smoothing_size)
      {
        if (normal_smoothing_size <= 0)
        {
          PCL_ERROR ("[pcl::%s::setNormalSmoothingSize] Invalid normal smoothing size given! (%f). Allowed ranges are: 0 < N. Defaulting to %f.\n", 
                      feature_name_.c_str (), normal_smoothing_size, normal_smoothing_size_);
          return;
        }
        normal_smoothing_size_ = normal_smoothing_size;
      }

      void
      setNormalEstimationMethod (NormalEstimationMethod normal_estimation_method)
      {
        normal_estimation_method_ = normal_estimation_method;
      }

      void
      setDepthDependentSmoothing (bool use_depth_dependent_smoothing)
      {
        use_depth_dependent_smoothing_ = use_depth_dependent_smoothing;
      }

      virtual inline void
      setInputCloud (const typename PointCloudIn::ConstPtr &cloud)
      {
        input_ = cloud;
        if (!cloud->isOrganized ())
        {
          PCL_ERROR ("[pcl::IntegralImageNormalEstimation::setInputCloud] Input dataset is not organized (height = 1).\n");
          return;
        }

        init_covariance_matrix_ = init_average_3d_gradient_ = init_depth_change_ = false;
        
        if (use_sensor_origin_)
        {
          vpx_ = input_->sensor_origin_.coeff (0);
          vpy_ = input_->sensor_origin_.coeff (1);
          vpz_ = input_->sensor_origin_.coeff (2);
        }

        // Initialize the correct data structure based on the normal estimation method chosen
        initData ();
      }

      inline float*
      getDistanceMap ()
      {
        return (distance_map_);
      }

      inline void
      setViewPoint (float vpx, float vpy, float vpz)
      {
        vpx_ = vpx;
        vpy_ = vpy;
        vpz_ = vpz;
        use_sensor_origin_ = false;
      }

      inline void
      getViewPoint (float &vpx, float &vpy, float &vpz)
      {
        vpx = vpx_;
        vpy = vpy_;
        vpz = vpz_;
      }

      inline void
      useSensorOriginAsViewPoint ()
      {
        use_sensor_origin_ = true;
        if (input_)
        {
          vpx_ = input_->sensor_origin_.coeff (0);
          vpy_ = input_->sensor_origin_.coeff (1);
          vpz_ = input_->sensor_origin_.coeff (2);
        }
        else
        {
          vpx_ = 0;
          vpy_ = 0;
          vpz_ = 0;
        }
      }
      
    protected:

      void
      computeFeature (PointCloudOut &output);

      void
      initData ();

    private:

      inline void
      flipNormalTowardsViewpoint (const PointInT &point, 
                                  float vp_x, float vp_y, float vp_z,
                                  float &nx, float &ny, float &nz)
      {
        // See if we need to flip any plane normals
        vp_x -= point.x;
        vp_y -= point.y;
        vp_z -= point.z;

        // Dot product between the (viewpoint - point) and the plane normal
        float cos_theta = (vp_x * nx + vp_y * ny + vp_z * nz);

        // Flip the plane normal
        if (cos_theta < 0)
        {
          nx *= -1;
          ny *= -1;
          nz *= -1;
        }
      }

      NormalEstimationMethod normal_estimation_method_;

      BorderPolicy border_policy_;

      int rect_width_;
      int rect_width_2_;
      int rect_width_4_;
      int rect_height_;
      int rect_height_2_;
      int rect_height_4_;

      float distance_threshold_;

      IntegralImage2D<float, 3> integral_image_DX_;
      IntegralImage2D<float, 3> integral_image_DY_;
      IntegralImage2D<float, 1> integral_image_depth_;
      IntegralImage2D<float, 3> integral_image_XYZ_;

      float *diff_x_;
      float *diff_y_;

      float *depth_data_;

      float *distance_map_;

      bool use_depth_dependent_smoothing_;

      float max_depth_change_factor_;

      float normal_smoothing_size_;

      bool init_covariance_matrix_;

      bool init_average_3d_gradient_;

      bool init_simple_3d_gradient_;

      bool init_depth_change_;

      float vpx_, vpy_, vpz_;

      bool use_sensor_origin_;
      
      bool
      initCompute ();

      void
      initCovarianceMatrixMethod ();

      void
      initAverage3DGradientMethod ();

      void
      initAverageDepthChangeMethod ();

      void
      initSimple3DGradientMethod ();

    public:
      EIGEN_MAKE_ALIGNED_OPERATOR_NEW
  };
}
#if defined BUILD_Maintainer && defined __GNUC__ && __GNUC__ == 4 && __GNUC_MINOR__ > 3
#pragma GCC diagnostic warning "-Weffc++"
#endif

#ifdef PCL_NO_PRECOMPILE
#include <pcl/features/impl/integral_image_normal.hpp>
#endif

#endif