void ColorizationFilter::filter(PointView& view) { PointRef point = view.point(0); for (PointId idx = 0; idx < view.size(); ++idx) { point.setPointId(idx); processOne(point); } }
void NormalFilter::filter(PointView& view) { KD3Index& kdi = view.build3dIndex(); for (PointId i = 0; i < view.size(); ++i) { // find the k-nearest neighbors auto ids = kdi.neighbors(i, m_knn); // compute covariance of the neighborhood auto B = eigen::computeCovariance(view, ids); // perform the eigen decomposition Eigen::SelfAdjointEigenSolver<Eigen::Matrix3f> solver(B); if (solver.info() != Eigen::Success) throwError("Cannot perform eigen decomposition."); auto eval = solver.eigenvalues(); Eigen::Vector3f normal = solver.eigenvectors().col(0); if (m_viewpointArg->set()) { PointRef p = view.point(i); Eigen::Vector3f vp( m_viewpoint.x - p.getFieldAs<double>(Dimension::Id::X), m_viewpoint.y - p.getFieldAs<double>(Dimension::Id::Y), m_viewpoint.z - p.getFieldAs<double>(Dimension::Id::Z)); if (vp.dot(normal) < 0) normal *= -1.0; } else if (m_up) { if (normal[2] < 0) normal *= -1.0; } view.setField(Dimension::Id::NormalX, i, normal[0]); view.setField(Dimension::Id::NormalY, i, normal[1]); view.setField(Dimension::Id::NormalZ, i, normal[2]); double sum = eval[0] + eval[1] + eval[2]; view.setField(Dimension::Id::Curvature, i, sum ? std::fabs(eval[0] / sum) : 0); } }