本文整理汇总了C++中NormalEstimation::computeEigen方法的典型用法代码示例。如果您正苦于以下问题：C++ NormalEstimation::computeEigen方法的具体用法？C++ NormalEstimation::computeEigen怎么用？C++ NormalEstimation::computeEigen使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类NormalEstimation的用法示例。
在下文中一共展示了NormalEstimation::computeEigen方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: TEST
TEST (PCL, NormalEstimationEigen)
{
Eigen::Vector4f plane_parameters;
float curvature;
NormalEstimation<PointXYZ, Eigen::MatrixXf> n;
// computePointNormal (indices, Vector)
computePointNormal (cloud, indices, plane_parameters, curvature);
EXPECT_NEAR (fabs (plane_parameters[0]), 0.035592, 1e-4);
EXPECT_NEAR (fabs (plane_parameters[1]), 0.369596, 1e-4);
EXPECT_NEAR (fabs (plane_parameters[2]), 0.928511, 1e-4);
EXPECT_NEAR (fabs (plane_parameters[3]), 0.0622552, 1e-4);
EXPECT_NEAR (curvature, 0.0693136, 1e-4);
float nx, ny, nz;
// computePointNormal (indices)
n.computePointNormal (cloud, indices, nx, ny, nz, curvature);
EXPECT_NEAR (fabs (nx), 0.035592, 1e-4);
EXPECT_NEAR (fabs (ny), 0.369596, 1e-4);
EXPECT_NEAR (fabs (nz), 0.928511, 1e-4);
EXPECT_NEAR (curvature, 0.0693136, 1e-4);
// computePointNormal (Vector)
computePointNormal (cloud, plane_parameters, curvature);
EXPECT_NEAR (plane_parameters[0], 0.035592, 1e-4);
EXPECT_NEAR (plane_parameters[1], 0.369596, 1e-4);
EXPECT_NEAR (plane_parameters[2], 0.928511, 1e-4);
EXPECT_NEAR (plane_parameters[3], -0.0622552, 1e-4);
EXPECT_NEAR (curvature, 0.0693136, 1e-4);
// flipNormalTowardsViewpoint (Vector)
flipNormalTowardsViewpoint (cloud.points[0], 0, 0, 0, plane_parameters);
EXPECT_NEAR (plane_parameters[0], -0.035592, 1e-4);
EXPECT_NEAR (plane_parameters[1], -0.369596, 1e-4);
EXPECT_NEAR (plane_parameters[2], -0.928511, 1e-4);
EXPECT_NEAR (plane_parameters[3], 0.0799743, 1e-4);
// flipNormalTowardsViewpoint
flipNormalTowardsViewpoint (cloud.points[0], 0, 0, 0, nx, ny, nz);
EXPECT_NEAR (nx, -0.035592, 1e-4);
EXPECT_NEAR (ny, -0.369596, 1e-4);
EXPECT_NEAR (nz, -0.928511, 1e-4);
// Object
PointCloud<Eigen::MatrixXf>::Ptr normals (new PointCloud<Eigen::MatrixXf> ());
// set parameters
PointCloud<PointXYZ>::Ptr cloudptr = cloud.makeShared ();
n.setInputCloud (cloudptr);
EXPECT_EQ (n.getInputCloud (), cloudptr);
boost::shared_ptr<vector<int> > indicesptr (new vector<int> (indices));
n.setIndices (indicesptr);
EXPECT_EQ (n.getIndices (), indicesptr);
n.setSearchMethod (tree);
EXPECT_EQ (n.getSearchMethod (), tree);
n.setKSearch (static_cast<int> (indices.size ()));
// estimate
n.computeEigen (*normals);
EXPECT_EQ (normals->points.rows (), indices.size ());
for (int i = 0; i < normals->points.rows (); ++i)
{
EXPECT_NEAR (normals->points.row (i)[0], -0.035592, 1e-4);
EXPECT_NEAR (normals->points.row (i)[1], -0.369596, 1e-4);
EXPECT_NEAR (normals->points.row (i)[2], -0.928511, 1e-4);
EXPECT_NEAR (normals->points.row (i)[3], 0.0693136, 1e-4);
}
PointCloud<PointXYZ>::Ptr surfaceptr = cloudptr;
n.setSearchSurface (surfaceptr);
EXPECT_EQ (n.getSearchSurface (), surfaceptr);
// Additional test for searchForNeigbhors
surfaceptr.reset (new PointCloud<PointXYZ>);
*surfaceptr = *cloudptr;
surfaceptr->points.resize (640 * 480);
surfaceptr->width = 640;
surfaceptr->height = 480;
EXPECT_EQ (surfaceptr->points.size (), surfaceptr->width * surfaceptr->height);
n.setSearchSurface (surfaceptr);
tree.reset ();
n.setSearchMethod (tree);
// estimate
n.computeEigen (*normals);
EXPECT_EQ (normals->points.rows (), indices.size ());
}