39 #ifndef PCL_SURFACE_IMPL_MARCHING_CUBES_RBF_H_
40 #define PCL_SURFACE_IMPL_MARCHING_CUBES_RBF_H_
42 #include <pcl/surface/marching_cubes_rbf.h>
43 #include <pcl/common/common.h>
44 #include <pcl/common/vector_average.h>
45 #include <pcl/Vertices.h>
46 #include <pcl/kdtree/kdtree_flann.h>
49 template <
typename Po
intNT>
55 template <
typename Po
intNT>
void
59 const unsigned int N =
static_cast<unsigned int> (input_->size ());
60 Eigen::MatrixXd M (2*N, 2*N),
63 for (
unsigned int row_i = 0; row_i < 2*N; ++row_i)
66 bool row_off = (row_i >= N) ? 1 : 0;
67 for (
unsigned int col_i = 0; col_i < 2*N; ++col_i)
70 bool col_off = (col_i >= N) ? 1 : 0;
71 M (row_i, col_i) =
kernel (Eigen::Vector3f (input_->points[col_i%N].getVector3fMap ()).cast<double> () + Eigen::Vector3f (input_->points[col_i%N].getNormalVector3fMap ()).cast<double> () * col_off * off_surface_epsilon_,
72 Eigen::Vector3f (input_->points[row_i%N].getVector3fMap ()).cast<double> () + Eigen::Vector3f (input_->points[row_i%N].getNormalVector3fMap ()).cast<double> () * row_off * off_surface_epsilon_);
75 d (row_i, 0) = row_off * off_surface_epsilon_;
79 Eigen::MatrixXd w (2*N, 1);
82 w = M.fullPivLu ().solve (d);
84 std::vector<double> weights (2*N);
85 std::vector<Eigen::Vector3d, Eigen::aligned_allocator<Eigen::Vector3d> > centers (2*N);
86 for (
unsigned int i = 0; i < N; ++i)
88 centers[i] = Eigen::Vector3f (input_->points[i].getVector3fMap ()).cast<double> ();
89 centers[i + N] = Eigen::Vector3f (input_->points[i].getVector3fMap ()).cast<double> () + Eigen::Vector3f (input_->points[i].getNormalVector3fMap ()).cast<double> () * off_surface_epsilon_;
90 weights[i] = w (i, 0);
91 weights[i + N] = w (i + N, 0);
94 for (
int x = 0; x < res_x_; ++x)
95 for (
int y = 0; y < res_y_; ++y)
96 for (
int z = 0; z < res_z_; ++z)
98 const Eigen::Vector3f point_f = (size_voxel_ * Eigen::Array3f (x, y, z)
99 + lower_boundary_).matrix ();
100 const Eigen::Vector3d point = point_f.cast<
double> ();
103 std::vector<double>::const_iterator w_it (weights.begin());
104 for (std::vector<Eigen::Vector3d, Eigen::aligned_allocator<Eigen::Vector3d> >::const_iterator c_it = centers.begin ();
105 c_it != centers.end (); ++c_it, ++w_it)
106 f += *w_it *
kernel (*c_it, point);
108 grid_[x * res_y_*res_z_ + y * res_z_ + z] = float (f);
113 template <
typename Po
intNT>
double
116 double r = (x - c).norm ();
120 #define PCL_INSTANTIATE_MarchingCubesRBF(T) template class PCL_EXPORTS pcl::MarchingCubesRBF<T>;
122 #endif // PCL_SURFACE_IMPL_MARCHING_CUBES_HOPPE_H_
void voxelizeData()
Convert the point cloud into voxel data.
~MarchingCubesRBF()
Destructor.
double kernel(Eigen::Vector3d c, Eigen::Vector3d x)
the Radial Basis Function kernel.