52 const Eigen::Vector3f &point,
float mean_intensity,
const Eigen::Vector3f &normal, Eigen::Vector3f &gradient)
54 if (indices.size () < 3)
56 gradient[0] = gradient[1] = gradient[2] = std::numeric_limits<float>::quiet_NaN ();
60 Eigen::Matrix3f
A = Eigen::Matrix3f::Zero ();
61 Eigen::Vector3f b = Eigen::Vector3f::Zero ();
66 if (!std::isfinite (p.x) ||
67 !std::isfinite (p.y) ||
68 !std::isfinite (p.z) ||
69 !std::isfinite (intensity_ (p)))
77 A (0, 0) += p.x * p.x;
78 A (0, 1) += p.x * p.y;
79 A (0, 2) += p.x * p.z;
81 A (1, 1) += p.y * p.y;
82 A (1, 2) += p.y * p.z;
84 A (2, 2) += p.z * p.z;
86 b[0] += p.x * intensity_ (p);
87 b[1] += p.y * intensity_ (p);
88 b[2] += p.z * intensity_ (p);
97 Eigen::Vector3f eigen_values;
103 if ( eigen_values (0) != 0)
104 b (0) /= eigen_values (0);
108 if ( eigen_values (1) != 0)
109 b (1) /= eigen_values (1);
113 if ( eigen_values (2) != 0)
114 b (2) /= eigen_values (2);
138 gradient = (Eigen::Matrix3f::Identity () - normal*normal.transpose ()) * x;
152 if (surface_->is_dense)
154#pragma omp parallel for \
157 firstprivate(nn_indices, nn_dists) \
158 num_threads(threads_)
164 if (!this->searchForNeighbors ((*indices_)[idx], search_parameter_,
nn_indices,
nn_dists))
166 p_out.gradient[0] =
p_out.gradient[1] =
p_out.gradient[2] = std::numeric_limits<float>::quiet_NaN ();
171 Eigen::Vector3f centroid;
177 centroid += (*surface_)[
nn_index].getVector3fMap ();
183 Eigen::Vector3f normal = Eigen::Vector3f::Map ((*normals_)[(*indices_) [idx]].normal);
184 Eigen::Vector3f gradient;
187 p_out.gradient[0] = gradient[0];
188 p_out.gradient[1] = gradient[1];
189 p_out.gradient[2] = gradient[2];
194#pragma omp parallel for \
197 firstprivate(nn_indices, nn_dists) \
198 num_threads(threads_)
203 if (!
isFinite ((*surface_) [(*indices_)[idx]]) ||
204 !this->searchForNeighbors ((*indices_)[idx], search_parameter_,
nn_indices,
nn_dists))
206 p_out.gradient[0] =
p_out.gradient[1] =
p_out.gradient[2] = std::numeric_limits<float>::quiet_NaN ();
210 Eigen::Vector3f centroid;
221 centroid += surface_->points [
nn_index].getVector3fMap ();
225 centroid /=
static_cast<float> (cp);
227 Eigen::Vector3f normal = Eigen::Vector3f::Map ((*normals_)[(*indices_) [idx]].normal);
228 Eigen::Vector3f gradient;
231 p_out.gradient[0] = gradient[0];
232 p_out.gradient[1] = gradient[1];
233 p_out.gradient[2] = gradient[2];
void eigen33(const Matrix &mat, typename Matrix::Scalar &eigenvalue, Vector &eigenvector)
determines the eigenvector and eigenvalue of the smallest eigenvalue of the symmetric positive semi d...