Point Cloud Library (PCL)
1.14.1-dev
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The pcl_surface library deals with reconstructing the original surfaces from 3D scans. Depending on the task at hand, this can be for example the hull, a mesh representation or a smoothed/resampled surface with normals.
Smoothing and resampling can be important if the cloud is noisy, or if it is composed of multiple scans that are not aligned perfectly. The complexity of the surface estimation can be adjusted, and normals can be estimated in the same step if needed.
Meshing is a general way to create a surface out of points, and currently there are two algorithms provided: a very fast triangulation of the original points, and a slower meshing that does smoothing and hole filling as well.
Creating a convex or concave hull is useful for example when there is a need for a simplified surface representation or when boundaries need to be extracted.
Please visit the tutorials on http://www.pointclouds.org for more information.
Classes | |
class | pcl::ConcaveHull< PointInT > |
ConcaveHull (alpha shapes) using libqhull library. More... | |
class | pcl::ConvexHull< PointInT > |
ConvexHull using libqhull library. More... | |
class | pcl::EarClipping |
The ear clipping triangulation algorithm. More... | |
class | pcl::GreedyProjectionTriangulation< PointInT > |
GreedyProjectionTriangulation is an implementation of a greedy triangulation algorithm for 3D points based on local 2D projections. More... | |
class | pcl::GridProjection< PointNT > |
Grid projection surface reconstruction method. More... | |
class | pcl::MarchingCubes< PointNT > |
The marching cubes surface reconstruction algorithm. More... | |
class | pcl::MarchingCubesHoppe< PointNT > |
The marching cubes surface reconstruction algorithm, using a signed distance function based on the distance from tangent planes, proposed by Hoppe et. More... | |
class | pcl::MarchingCubesRBF< PointNT > |
The marching cubes surface reconstruction algorithm, using a signed distance function based on radial basis functions. More... | |
class | pcl::MovingLeastSquares< PointInT, PointOutT > |
MovingLeastSquares represent an implementation of the MLS (Moving Least Squares) algorithm for data smoothing and improved normal estimation. More... | |
class | pcl::OrganizedFastMesh< PointInT > |
Simple triangulation/surface reconstruction for organized point clouds. More... | |
class | pcl::Poisson< PointNT > |
The Poisson surface reconstruction algorithm. More... | |
class | pcl::CloudSurfaceProcessing< PointInT, PointOutT > |
CloudSurfaceProcessing represents the base class for algorithms that takes a point cloud as input and produces a new output cloud that has been modified towards a better surface representation. More... | |
class | pcl::MeshProcessing |
MeshProcessing represents the base class for mesh processing algorithms. More... | |
class | pcl::PCLSurfaceBase< PointInT > |
Pure abstract class. More... | |
class | pcl::SurfaceReconstruction< PointInT > |
SurfaceReconstruction represents a base surface reconstruction class. More... | |
class | pcl::MeshConstruction< PointInT > |
MeshConstruction represents a base surface reconstruction class. More... | |
class | pcl::TextureMapping< PointInT > |
The texture mapping algorithm. More... | |
Functions | |
bool | pcl::comparePoints2D (const std::pair< int, Eigen::Vector4f > &p1, const std::pair< int, Eigen::Vector4f > &p2) |
Sort 2D points in a vector structure. More... | |
bool | pcl::isVisible (const Eigen::Vector2f &X, const Eigen::Vector2f &S1, const Eigen::Vector2f &S2, const Eigen::Vector2f &R=Eigen::Vector2f::Zero()) |
Returns if a point X is visible from point R (or the origin) when taking into account the segment between the points S1 and S2. More... | |
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inline |
#include <pcl/surface/convex_hull.h>
Sort 2D points in a vector structure.
p1 | the first point |
p2 | the second point |
Definition at line 59 of file convex_hull.h.
References M_PI.
Referenced by pcl::ConvexHull< PointInT >::performReconstruction2D().
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inline |
#include <pcl/surface/gp3.h>
Returns if a point X is visible from point R (or the origin) when taking into account the segment between the points S1 and S2.
X | 2D coordinate of the point |
S1 | 2D coordinate of the segment's first point |
S2 | 2D coordinate of the segment's second point |
R | 2D coordinate of the reference point (defaults to 0,0) |