A point cloud consists of point coordinates, and optionally point colors and point normals. More...

#include <PointCloud.h>

Inheritance diagram for open3d::geometry::PointCloud:

Public Member Functions
	PointCloud ()
	Default Constructor. More...

	PointCloud (const std::vector< Eigen::Vector3d > &points)
	Parameterized Constructor. More...

	~PointCloud () override

PointCloud &	Clear () override
	Clear all elements in the geometry. More...

bool	IsEmpty () const override
	Returns `true` iff the geometry is empty. More...

Eigen::Vector3d	GetMinBound () const override
	Returns min bounds for geometry coordinates. More...

Eigen::Vector3d	GetMaxBound () const override
	Returns max bounds for geometry coordinates. More...

Eigen::Vector3d	GetCenter () const override
	Returns the center of the geometry coordinates. More...

AxisAlignedBoundingBox	GetAxisAlignedBoundingBox () const override

OrientedBoundingBox	GetOrientedBoundingBox (bool robust=false) const override

OrientedBoundingBox	GetMinimalOrientedBoundingBox (bool robust=false) const override

PointCloud &	Transform (const Eigen::Matrix4d &transformation) override
	Apply transformation (4x4 matrix) to the geometry coordinates. More...

PointCloud &	Translate (const Eigen::Vector3d &translation, bool relative=true) override
	Apply translation to the geometry coordinates. More...

PointCloud &	Scale (const double scale, const Eigen::Vector3d &center) override
	Apply scaling to the geometry coordinates. Given a scaling factor \(s\), and center \(c\), a given point \(p\) is transformed according to \(s (p - c) + c\). More...

PointCloud &	Rotate (const Eigen::Matrix3d &R, const Eigen::Vector3d &center) override
	Apply rotation to the geometry coordinates and normals. Given a rotation matrix \(R\), and center \(c\), a given point \(p\) is transformed according to \(R (p - c) + c\). More...

PointCloud &	operator+= (const PointCloud &cloud)

PointCloud	operator+ (const PointCloud &cloud) const

bool	HasPoints () const
	Returns 'true' if the point cloud contains points. More...

bool	HasNormals () const
	Returns `true` if the point cloud contains point normals. More...

bool	HasColors () const
	Returns `true` if the point cloud contains point colors. More...

bool	HasCovariances () const
	Returns 'true' if the point cloud contains per-point covariance matrix. More...

PointCloud &	NormalizeNormals ()
	Normalize point normals to length 1. More...

PointCloud &	PaintUniformColor (const Eigen::Vector3d &color)

PointCloud &	RemoveNonFinitePoints (bool remove_nan=true, bool remove_infinite=true)
	Removes all points from the point cloud that have a nan entry, or infinite entries. It also removes the corresponding attributes associated with the non-finite point such as normals, covariances and color entries. It doesn't re-computes these attributes after removing non-finite points. More...

PointCloud &	RemoveDuplicatedPoints ()
	Removes duplicated points, i.e., points that have identical coordinates. It also removes the corresponding attributes associated with the non-finite point such as normals, covariances and color entries. It doesn't re-computes these attributes after removing duplicated points. More...

std::shared_ptr< PointCloud >	SelectByIndex (const std::vector< size_t > &indices, bool invert=false) const
	Selects points from `input` pointcloud, with indices in `indices`, and returns a new point-cloud with selected points. More...

std::shared_ptr< PointCloud >	VoxelDownSample (double voxel_size) const
	Downsample input pointcloud with a voxel, and return a new point-cloud. Normals, covariances and colors are averaged if they exist. More...

std::tuple< std::shared_ptr< PointCloud >, Eigen::MatrixXi, std::vector< std::vector< int > > >	VoxelDownSampleAndTrace (double voxel_size, const Eigen::Vector3d &min_bound, const Eigen::Vector3d &max_bound, bool approximate_class=false) const
	Function to downsample using geometry.PointCloud.VoxelDownSample. More...

std::shared_ptr< PointCloud >	UniformDownSample (size_t every_k_points) const
	Function to downsample input pointcloud into output pointcloud uniformly. More...

std::shared_ptr< PointCloud >	RandomDownSample (double sampling_ratio) const
	Function to downsample input pointcloud into output pointcloud randomly. More...

std::shared_ptr< PointCloud >	FarthestPointDownSample (size_t num_samples) const
	Function to downsample input pointcloud into output pointcloud with a set of points has farthest distance. More...

std::shared_ptr< PointCloud >	Crop (const AxisAlignedBoundingBox &bbox, bool invert=false) const
	Function to crop pointcloud into output pointcloud. More...

std::shared_ptr< PointCloud >	Crop (const OrientedBoundingBox &bbox, bool invert=false) const
	Function to crop pointcloud into output pointcloud. More...

std::tuple< std::shared_ptr< PointCloud >, std::vector< size_t > >	RemoveRadiusOutliers (size_t nb_points, double search_radius, bool print_progress=false) const
	Function to remove points that have less than `nb_points` in a sphere of a given radius. More...

std::tuple< std::shared_ptr< PointCloud >, std::vector< size_t > >	RemoveStatisticalOutliers (size_t nb_neighbors, double std_ratio, bool print_progress=false) const
	Function to remove points that are further away from their `nb_neighbor` neighbors in average. More...

void	EstimateNormals (const KDTreeSearchParam &search_param=KDTreeSearchParamKNN(), bool fast_normal_computation=true)
	Function to compute the normals of a point cloud. More...

void	OrientNormalsToAlignWithDirection (const Eigen::Vector3d &orientation_reference=Eigen::Vector3d(0.0, 0.0, 1.0))
	Function to orient the normals of a point cloud. More...

void	OrientNormalsTowardsCameraLocation (const Eigen::Vector3d &camera_location=Eigen::Vector3d::Zero())
	Function to orient the normals of a point cloud. More...

void	OrientNormalsConsistentTangentPlane (size_t k, const double lambda=0.0, const double cos_alpha_tol=1.0)
	Function to consistently orient estimated normals based on consistent tangent planes as described in Hoppe et al., "Surface Reconstruction from Unorganized Points", 1992. Further details on parameters are described in Piazza, Valentini, Varetti, "Mesh Reconstruction from Point Cloud", 2023. More...

std::vector< double >	ComputePointCloudDistance (const PointCloud &target)
	Function to compute the point to point distances between point clouds. More...

void	EstimateCovariances (const KDTreeSearchParam &search_param=KDTreeSearchParamKNN())
	Function to compute the covariance matrix for each point of a point cloud. More...

std::tuple< Eigen::Vector3d, Eigen::Matrix3d >	ComputeMeanAndCovariance () const

std::vector< double >	ComputeMahalanobisDistance () const
	Function to compute the Mahalanobis distance for points in an input point cloud. More...

std::vector< double >	ComputeNearestNeighborDistance () const

std::tuple< std::shared_ptr< TriangleMesh >, std::vector< size_t > >	ComputeConvexHull (bool joggle_inputs=false) const

std::tuple< std::shared_ptr< TriangleMesh >, std::vector< size_t > >	HiddenPointRemoval (const Eigen::Vector3d &camera_location, const double radius) const
	This is an implementation of the Hidden Point Removal operator described in Katz et. al. 'Direct Visibility of Point Sets', 2007. More...

std::vector< int >	ClusterDBSCAN (double eps, size_t min_points, bool print_progress=false) const
	Cluster PointCloud using the DBSCAN algorithm Ester et al., "A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise", 1996. More...

std::tuple< Eigen::Vector4d, std::vector< size_t > >	SegmentPlane (const double distance_threshold=0.01, const int ransac_n=3, const int num_iterations=100, const double probability=0.99999999) const
	Segment PointCloud plane using the RANSAC algorithm. More...

std::vector< std::shared_ptr< OrientedBoundingBox > >	DetectPlanarPatches (double normal_variance_threshold_deg=60, double coplanarity_deg=75, double outlier_ratio=0.75, double min_plane_edge_length=0.0, size_t min_num_points=0, const geometry::KDTreeSearchParam &search_param=geometry::KDTreeSearchParamKNN()) const
	Robustly detect planar patches in the point cloud using. Araújo and Oliveira, “A robust statistics approach for plane detection in unorganized point clouds,” Pattern Recognition, 2020. More...

Public Member Functions inherited from open3d::geometry::Geometry3D
	~Geometry3D () override

virtual Geometry3D &	Rotate (const Eigen::Matrix3d &R)

Public Member Functions inherited from open3d::geometry::Geometry
virtual	~Geometry ()

GeometryType	GetGeometryType () const
	Returns one of registered geometry types. More...

int	Dimension () const
	Returns whether the geometry is 2D or 3D. More...

std::string	GetName () const

void	SetName (const std::string &name)

Static Public Member Functions
static std::vector< Eigen::Matrix3d >	EstimatePerPointCovariances (const PointCloud &input, const KDTreeSearchParam &search_param=KDTreeSearchParamKNN())
	Static function to compute the covariance matrix for each point of a point cloud. Doesn't change the input PointCloud, just outputs the covariance matrices. More...

static std::shared_ptr< PointCloud >	CreateFromDepthImage (const Image &depth, const camera::PinholeCameraIntrinsic &intrinsic, const Eigen::Matrix4d &extrinsic=Eigen::Matrix4d::Identity(), double depth_scale=1000.0, double depth_trunc=1000.0, int stride=1, bool project_valid_depth_only=true)
	Factory function to create a pointcloud from a depth image and a camera model. More...

static std::shared_ptr< PointCloud >	CreateFromRGBDImage (const RGBDImage &image, const camera::PinholeCameraIntrinsic &intrinsic, const Eigen::Matrix4d &extrinsic=Eigen::Matrix4d::Identity(), bool project_valid_depth_only=true)
	Factory function to create a pointcloud from an RGB-D image and a camera model. More...

static std::shared_ptr< PointCloud >	CreateFromVoxelGrid (const VoxelGrid &voxel_grid)
	Factory Function to create a PointCloud from a VoxelGrid. More...

Static Public Member Functions inherited from open3d::geometry::Geometry3D
static Eigen::Matrix3d	GetRotationMatrixFromXYZ (const Eigen::Vector3d &rotation)
	Get Rotation Matrix from XYZ RotationType. More...

static Eigen::Matrix3d	GetRotationMatrixFromYZX (const Eigen::Vector3d &rotation)
	Get Rotation Matrix from YZX RotationType. More...

static Eigen::Matrix3d	GetRotationMatrixFromZXY (const Eigen::Vector3d &rotation)
	Get Rotation Matrix from ZXY RotationType. More...

static Eigen::Matrix3d	GetRotationMatrixFromXZY (const Eigen::Vector3d &rotation)
	Get Rotation Matrix from XZY RotationType. More...

static Eigen::Matrix3d	GetRotationMatrixFromZYX (const Eigen::Vector3d &rotation)
	Get Rotation Matrix from ZYX RotationType. More...

static Eigen::Matrix3d	GetRotationMatrixFromYXZ (const Eigen::Vector3d &rotation)
	Get Rotation Matrix from YXZ RotationType. More...

static Eigen::Matrix3d	GetRotationMatrixFromAxisAngle (const Eigen::Vector3d &rotation)
	Get Rotation Matrix from AxisAngle RotationType. More...

static Eigen::Matrix3d	GetRotationMatrixFromQuaternion (const Eigen::Vector4d &rotation)
	Get Rotation Matrix from Quaternion. More...

Data Fields
std::vector< Eigen::Vector3d >	points_
	Points coordinates. More...

std::vector< Eigen::Vector3d >	normals_
	Points normals. More...

std::vector< Eigen::Vector3d >	colors_
	RGB colors of points. More...

std::vector< Eigen::Matrix3d >	covariances_
	Covariance Matrix for each point. More...

Additional Inherited Members
Public Types inherited from open3d::geometry::Geometry
enum class	GeometryType { Unspecified = 0 , PointCloud = 1 , VoxelGrid = 2 , Octree = 3 , LineSet = 4 , MeshBase = 5 , TriangleMesh = 6 , HalfEdgeTriangleMesh = 7 , Image = 8 , RGBDImage = 9 , TetraMesh = 10 , OrientedBoundingBox = 11 , AxisAlignedBoundingBox = 12 }
	Specifies possible geometry types. More...

Protected Member Functions inherited from open3d::geometry::Geometry3D
	Geometry3D (GeometryType type)
	Parameterized Constructor. More...

Eigen::Vector3d	ComputeMinBound (const std::vector< Eigen::Vector3d > &points) const
	Compute min bound of a list points. More...

Eigen::Vector3d	ComputeMaxBound (const std::vector< Eigen::Vector3d > &points) const
	Compute max bound of a list points. More...

Eigen::Vector3d	ComputeCenter (const std::vector< Eigen::Vector3d > &points) const
	Computer center of a list of points. More...

void	ResizeAndPaintUniformColor (std::vector< Eigen::Vector3d > &colors, const size_t size, const Eigen::Vector3d &color) const
	Resizes the colors vector and paints a uniform color. More...

void	TransformPoints (const Eigen::Matrix4d &transformation, std::vector< Eigen::Vector3d > &points) const
	Transforms all points with the transformation matrix. More...

void	TransformNormals (const Eigen::Matrix4d &transformation, std::vector< Eigen::Vector3d > &normals) const
	Transforms the normals with the transformation matrix. More...

void	TransformCovariances (const Eigen::Matrix4d &transformation, std::vector< Eigen::Matrix3d > &covariances) const
	Transforms all covariance matrices with the transformation. More...

void	TranslatePoints (const Eigen::Vector3d &translation, std::vector< Eigen::Vector3d > &points, bool relative) const
	Apply translation to the geometry coordinates. More...

void	ScalePoints (const double scale, std::vector< Eigen::Vector3d > &points, const Eigen::Vector3d &center) const
	Scale the coordinates of all points by the scaling factor `scale`. More...

void	RotatePoints (const Eigen::Matrix3d &R, std::vector< Eigen::Vector3d > &points, const Eigen::Vector3d &center) const
	Rotate all points with the rotation matrix `R`. More...

void	RotateNormals (const Eigen::Matrix3d &R, std::vector< Eigen::Vector3d > &normals) const
	Rotate all normals with the rotation matrix `R`. More...

void	RotateCovariances (const Eigen::Matrix3d &R, std::vector< Eigen::Matrix3d > &covariances) const
	Rotate all covariance matrices with the rotation matrix `R`. More...

Protected Member Functions inherited from open3d::geometry::Geometry
	Geometry (GeometryType type, int dimension)
	Parameterized Constructor. More...

Detailed Description

A point cloud consists of point coordinates, and optionally point colors and point normals.

Constructor & Destructor Documentation

◆ PointCloud() [1/2]

open3d::geometry::PointCloud::PointCloud ( )

inline

Default Constructor.

◆ PointCloud() [2/2]

open3d::geometry::PointCloud::PointCloud ( const std::vector< Eigen::Vector3d > & points )

inline

Parameterized Constructor.

Parameters

points Points coordinates.

◆ ~PointCloud()

open3d::geometry::PointCloud::~PointCloud ( )

inlineoverride

Member Function Documentation

◆ Clear()

PointCloud & open3d::geometry::PointCloud::Clear ( )

overridevirtual

Clear all elements in the geometry.

Implements open3d::geometry::Geometry3D.

◆ ClusterDBSCAN()

std::vector< int > open3d::geometry::PointCloud::ClusterDBSCAN	(	double	eps,
		size_t	min_points,
		bool	print_progress = `false`
	)		const

Cluster PointCloud using the DBSCAN algorithm Ester et al., "A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise", 1996.

Returns a list of point labels, -1 indicates noise according to the algorithm.

Parameters

eps	Density parameter that is used to find neighbouring points.
min_points	Minimum number of points to form a cluster.
print_progress	If `true` the progress is visualized in the console.

◆ ComputeConvexHull()

std::tuple< std::shared_ptr< TriangleMesh >, std::vector< size_t > > open3d::geometry::PointCloud::ComputeConvexHull ( bool joggle_inputs = false ) const

Function that computes the convex hull of the point cloud using qhull

Parameters

joggle_inputs If true allows the algorithm to add random noise to the points to work around degenerate inputs. This adds the 'QJ' option to the qhull command.

Returns: The triangle mesh of the convex hull and the list of point indices that are part of the convex hull.

◆ ComputeMahalanobisDistance()

std::vector< double > open3d::geometry::PointCloud::ComputeMahalanobisDistance ( ) const

Function to compute the Mahalanobis distance for points in an input point cloud.

See: https://en.wikipedia.org/wiki/Mahalanobis_distance

◆ ComputeMeanAndCovariance()

std::tuple< Eigen::Vector3d, Eigen::Matrix3d > open3d::geometry::PointCloud::ComputeMeanAndCovariance ( ) const

Function to compute the mean and covariance matrix of a point cloud.

◆ ComputeNearestNeighborDistance()

std::vector< double > open3d::geometry::PointCloud::ComputeNearestNeighborDistance ( ) const

Function to compute the distance from a point to its nearest neighbor in the input point cloud

◆ ComputePointCloudDistance()

std::vector< double > open3d::geometry::PointCloud::ComputePointCloudDistance ( const PointCloud & target )

Function to compute the point to point distances between point clouds.

For each point in the source point cloud, compute the distance to the target point cloud.

Parameters

target The target point cloud.

◆ CreateFromDepthImage()

std::shared_ptr< PointCloud > open3d::geometry::PointCloud::CreateFromDepthImage	(	const Image &	depth,
		const camera::PinholeCameraIntrinsic &	intrinsic,
		const Eigen::Matrix4d &	extrinsic = `Eigen::Matrix4d::Identity()`,
		double	depth_scale = `1000.0`,
		double	depth_trunc = `1000.0`,
		int	stride = `1`,
		bool	project_valid_depth_only = `true`
	)

static

Factory function to create a pointcloud from a depth image and a camera model.

Given depth value d at (u, v) image coordinate, the corresponding 3d point is: z = d / depth_scale
x = (u - cx) * z / fx
y = (v - cy) * z / fy

Parameters

depth	The input depth image can be either a float image, or a uint16_t image.
intrinsic	Intrinsic parameters of the camera.
extrinsic	Extrinsic parameters of the camera.
depth_scale	The depth is scaled by 1 / `depth_scale`.
depth_trunc	Truncated at `depth_trunc` distance.
stride	Sampling factor to support coarse point cloud extraction.

Returns: An empty pointcloud if the conversion fails. If

Parameters

project_valid_depth_only is true, return point cloud, which doesn't have nan point. If the value is false, return point cloud, which has a point for each pixel, whereas invalid depth results in NaN points.

◆ CreateFromRGBDImage()

std::shared_ptr< PointCloud > open3d::geometry::PointCloud::CreateFromRGBDImage	(	const RGBDImage &	image,
		const camera::PinholeCameraIntrinsic &	intrinsic,
		const Eigen::Matrix4d &	extrinsic = `Eigen::Matrix4d::Identity()`,
		bool	project_valid_depth_only = `true`
	)

static

Factory function to create a pointcloud from an RGB-D image and a camera model.

Given depth value d at (u, v) image coordinate, the corresponding 3d point is: z = d / depth_scale
x = (u - cx) * z / fx
y = (v - cy) * z / fy

Parameters

image	The input image.
intrinsic	Intrinsic parameters of the camera.
extrinsic	Extrinsic parameters of the camera.

Returns: An empty pointcloud if the conversion fails. If

Parameters

project_valid_depth_only is true, return point cloud, which doesn't have nan point. If the value is false, return point cloud, which has a point for each pixel, whereas invalid depth results in NaN points.

◆ CreateFromVoxelGrid()

std::shared_ptr< PointCloud > open3d::geometry::PointCloud::CreateFromVoxelGrid ( const VoxelGrid & voxel_grid )

static

Factory Function to create a PointCloud from a VoxelGrid.

It transforms the voxel centers to 3D points using the original point cloud coordinate (with respect to the center of the voxel grid).

Parameters

voxel_grid The input VoxelGrid.

◆ Crop() [1/2]

std::shared_ptr< PointCloud > open3d::geometry::PointCloud::Crop	(	const AxisAlignedBoundingBox &	bbox,
		bool	invert = `false`
	)		const

Function to crop pointcloud into output pointcloud.

All points with coordinates outside the bounding box bbox are clipped.

Parameters

bbox	AxisAlignedBoundingBox to crop points.
invert	Optional boolean to invert cropping.

◆ Crop() [2/2]

std::shared_ptr< PointCloud > open3d::geometry::PointCloud::Crop	(	const OrientedBoundingBox &	bbox,
		bool	invert = `false`
	)		const

Function to crop pointcloud into output pointcloud.

All points with coordinates outside the bounding box bbox are clipped.

Parameters

bbox	OrientedBoundingBox to crop points.
invert	Optional boolean to invert cropping.

◆ DetectPlanarPatches()

std::vector< std::shared_ptr< OrientedBoundingBox > > open3d::geometry::PointCloud::DetectPlanarPatches	(	double	normal_variance_threshold_deg = `60`,
		double	coplanarity_deg = `75`,
		double	outlier_ratio = `0.75`,
		double	min_plane_edge_length = `0.0`,
		size_t	min_num_points = `0`,
		const geometry::KDTreeSearchParam &	search_param = `geometry::KDTreeSearchParamKNN()`
	)		const

Robustly detect planar patches in the point cloud using. Araújo and Oliveira, “A robust statistics approach for plane detection in unorganized point clouds,” Pattern Recognition, 2020.

Parameters

normal_variance_threshold_deg	Planes having point normals with high variance are rejected. The default value is 60 deg. Larger values would allow more noisy planes to be detected.
coplanarity_deg	The curvature of plane detections are scored using the angle between the plane's normal vector and an auxiliary vector. An ideal plane would have a score of 90 deg. The default value for this threshold is 75 deg, and detected planes with scores lower than this are rejected. Large threshold values encourage a tighter distribution of points around the detected plane, i.e., less curvature.
outlier_ratio	Maximum allowable ratio of outliers in associated plane points before plane is rejected.
min_plane_edge_length	A patch's largest edge must greater than this value to be considered a true planar patch. If set to 0, defaults to 1% of largest span of point cloud.
min_num_points	Determines how deep the associated octree becomes and how many points must be used for estimating a plane. If set to 0, defaults to 0.1% of the number of points in point cloud.
search_param	Point neighbors are used to grow and merge detected planes. Neighbors are found with KDTree search using these params. More neighbors results in higher quality patches at the cost of compute.

Returns: Returns a list of detected planar patches, represented as OrientedBoundingBox objects, with the third column (z) of R indicating the planar patch normal vector. The extent in the z direction is non-zero so that the OrientedBoundingBox contains the points that contribute to the plane detection.

◆ EstimateCovariances()

void open3d::geometry::PointCloud::EstimateCovariances ( const KDTreeSearchParam & search_param = KDTreeSearchParamKNN() )

Function to compute the covariance matrix for each point of a point cloud.

Parameters

search_param The KDTree search parameters for neighborhood search.

◆ EstimateNormals()

void open3d::geometry::PointCloud::EstimateNormals	(	const KDTreeSearchParam &	search_param = `KDTreeSearchParamKNN()`,
		bool	fast_normal_computation = `true`
	)

Function to compute the normals of a point cloud.

Normals are oriented with respect to the input point cloud if normals exist.

Parameters

search_param	The KDTree search parameters for neighborhood search.
fast_normal_computation	If true, the normal estimation uses a non-iterative method to extract the eigenvector from the covariance matrix. This is faster, but is not as numerical stable.

◆ EstimatePerPointCovariances()

std::vector< Eigen::Matrix3d > open3d::geometry::PointCloud::EstimatePerPointCovariances	(	const PointCloud &	input,
		const KDTreeSearchParam &	search_param = `KDTreeSearchParamKNN()`
	)

static

Static function to compute the covariance matrix for each point of a point cloud. Doesn't change the input PointCloud, just outputs the covariance matrices.

Parameters

input	PointCloud to use for covariance computation
search_param	The KDTree search parameters for neighborhood search.

◆ FarthestPointDownSample()

std::shared_ptr< PointCloud > open3d::geometry::PointCloud::FarthestPointDownSample ( size_t num_samples ) const

Function to downsample input pointcloud into output pointcloud with a set of points has farthest distance.

The sample is performed by selecting the farthest point from previous selected points iteratively.

Parameters

num_samples Number of points to be sampled.

◆ GetAxisAlignedBoundingBox()

AxisAlignedBoundingBox open3d::geometry::PointCloud::GetAxisAlignedBoundingBox ( ) const

overridevirtual

Creates the axis-aligned bounding box around the points of the object. Further details in AxisAlignedBoundingBox::CreateFromPoints()

Implements open3d::geometry::Geometry3D.

◆ GetCenter()

Eigen::Vector3d open3d::geometry::PointCloud::GetCenter ( ) const

overridevirtual

Returns the center of the geometry coordinates.

Implements open3d::geometry::Geometry3D.

◆ GetMaxBound()

Eigen::Vector3d open3d::geometry::PointCloud::GetMaxBound ( ) const

overridevirtual

Returns max bounds for geometry coordinates.

Implements open3d::geometry::Geometry3D.

◆ GetMinBound()

Eigen::Vector3d open3d::geometry::PointCloud::GetMinBound ( ) const

overridevirtual

Returns min bounds for geometry coordinates.

Implements open3d::geometry::Geometry3D.

◆ GetMinimalOrientedBoundingBox()

OrientedBoundingBox open3d::geometry::PointCloud::GetMinimalOrientedBoundingBox ( bool robust = false ) const

overridevirtual

Creates the minimal oriented bounding box around the points of the object. Further details in OrientedBoundingBox::CreateFromPointsMinimal()

Parameters

robust If set to true uses a more robust method which works in degenerate cases but introduces noise to the points coordinates.

Implements open3d::geometry::Geometry3D.

◆ GetOrientedBoundingBox()

OrientedBoundingBox open3d::geometry::PointCloud::GetOrientedBoundingBox ( bool robust = false ) const

overridevirtual

Creates an oriented bounding box around the points of the object. Further details in OrientedBoundingBox::CreateFromPoints()

Parameters

robust If set to true uses a more robust method which works in degenerate cases but introduces noise to the points coordinates.

Implements open3d::geometry::Geometry3D.

◆ HasColors()

bool open3d::geometry::PointCloud::HasColors ( ) const

inline

Returns true if the point cloud contains point colors.

◆ HasCovariances()

bool open3d::geometry::PointCloud::HasCovariances ( ) const

inline

Returns 'true' if the point cloud contains per-point covariance matrix.

◆ HasNormals()

bool open3d::geometry::PointCloud::HasNormals ( ) const

inline

Returns true if the point cloud contains point normals.

◆ HasPoints()

bool open3d::geometry::PointCloud::HasPoints ( ) const

inline

Returns 'true' if the point cloud contains points.

◆ HiddenPointRemoval()

std::tuple< std::shared_ptr< TriangleMesh >, std::vector< size_t > > open3d::geometry::PointCloud::HiddenPointRemoval	(	const Eigen::Vector3d &	camera_location,
		const double	radius
	)		const

This is an implementation of the Hidden Point Removal operator described in Katz et. al. 'Direct Visibility of Point Sets', 2007.

Additional information about the choice of radius for noisy point clouds can be found in Mehra et. al. 'Visibility of Noisy Point Cloud Data', 2010.

Parameters

camera_location	All points not visible from that location will be removed.
radius	The radius of the spherical projection.

◆ IsEmpty()

bool open3d::geometry::PointCloud::IsEmpty ( ) const

overridevirtual

Returns true iff the geometry is empty.

Implements open3d::geometry::Geometry3D.

◆ NormalizeNormals()

PointCloud& open3d::geometry::PointCloud::NormalizeNormals ( )

inline

Normalize point normals to length 1.

◆ operator+()

PointCloud open3d::geometry::PointCloud::operator+ ( const PointCloud & cloud ) const

◆ operator+=()

PointCloud & open3d::geometry::PointCloud::operator+= ( const PointCloud & cloud )

◆ OrientNormalsConsistentTangentPlane()

void open3d::geometry::PointCloud::OrientNormalsConsistentTangentPlane	(	size_t	k,
		const double	lambda = `0.0`,
		const double	cos_alpha_tol = `1.0`
	)

Function to consistently orient estimated normals based on consistent tangent planes as described in Hoppe et al., "Surface Reconstruction from Unorganized Points", 1992. Further details on parameters are described in Piazza, Valentini, Varetti, "Mesh Reconstruction from Point Cloud", 2023.

Parameters

k	k nearest neighbour for graph reconstruction for normal propagation.
lambda	penalty constant on the distance of a point from the tangent plane
cos_alpha_tol	treshold that defines the amplitude of the cone spanned by the reference normal

◆ OrientNormalsToAlignWithDirection()

void open3d::geometry::PointCloud::OrientNormalsToAlignWithDirection ( const Eigen::Vector3d & orientation_reference = Eigen::Vector3d(0.0, 0.0, 1.0) )

Function to orient the normals of a point cloud.

Parameters

orientation_reference Normals are oriented with respect to orientation_reference.

◆ OrientNormalsTowardsCameraLocation()

void open3d::geometry::PointCloud::OrientNormalsTowardsCameraLocation ( const Eigen::Vector3d & camera_location = Eigen::Vector3d::Zero() )

Function to orient the normals of a point cloud.

Parameters

camera_location Normals are oriented with towards the camera_location.

◆ PaintUniformColor()

PointCloud& open3d::geometry::PointCloud::PaintUniformColor ( const Eigen::Vector3d & color )

inline

Assigns each point in the PointCloud the same color.

Parameters

color RGB colors of points.

◆ RandomDownSample()

std::shared_ptr< PointCloud > open3d::geometry::PointCloud::RandomDownSample ( double sampling_ratio ) const

Function to downsample input pointcloud into output pointcloud randomly.

The sample is performed by randomly selecting the index of the points in the pointcloud.

Parameters

sampling_ratio Sampling ratio, the ratio of sample to total number of points in the pointcloud.

◆ RemoveDuplicatedPoints()

PointCloud & open3d::geometry::PointCloud::RemoveDuplicatedPoints ( )

Removes duplicated points, i.e., points that have identical coordinates. It also removes the corresponding attributes associated with the non-finite point such as normals, covariances and color entries. It doesn't re-computes these attributes after removing duplicated points.

◆ RemoveNonFinitePoints()

PointCloud & open3d::geometry::PointCloud::RemoveNonFinitePoints	(	bool	remove_nan = `true`,
		bool	remove_infinite = `true`
	)

Removes all points from the point cloud that have a nan entry, or infinite entries. It also removes the corresponding attributes associated with the non-finite point such as normals, covariances and color entries. It doesn't re-computes these attributes after removing non-finite points.

Parameters

remove_nan	Remove NaN values from the PointCloud.
remove_infinite	Remove infinite values from the PointCloud.

◆ RemoveRadiusOutliers()

std::tuple< std::shared_ptr< PointCloud >, std::vector< size_t > > open3d::geometry::PointCloud::RemoveRadiusOutliers	(	size_t	nb_points,
		double	search_radius,
		bool	print_progress = `false`
	)		const

Function to remove points that have less than nb_points in a sphere of a given radius.

Parameters

nb_points	Number of points within the radius.
search_radius	Radius of the sphere.
print_progress	Whether to print the progress bar.

◆ RemoveStatisticalOutliers()

std::tuple< std::shared_ptr< PointCloud >, std::vector< size_t > > open3d::geometry::PointCloud::RemoveStatisticalOutliers	(	size_t	nb_neighbors,
		double	std_ratio,
		bool	print_progress = `false`
	)		const

Function to remove points that are further away from their nb_neighbor neighbors in average.

Parameters

nb_neighbors	Number of neighbors around the target point.
std_ratio	Standard deviation ratio.

◆ Rotate()

PointCloud & open3d::geometry::PointCloud::Rotate	(	const Eigen::Matrix3d &	R,
		const Eigen::Vector3d &	center
	)

overridevirtual

Apply rotation to the geometry coordinates and normals. Given a rotation matrix \(R\), and center \(c\), a given point \(p\) is transformed according to \(R (p - c) + c\).

Parameters

R	A 3x3 rotation matrix
center	Rotation center that is used for the rotation.

Implements open3d::geometry::Geometry3D.

◆ Scale()

PointCloud & open3d::geometry::PointCloud::Scale	(	const double	scale,
		const Eigen::Vector3d &	center
	)

overridevirtual

Apply scaling to the geometry coordinates. Given a scaling factor \(s\), and center \(c\), a given point \(p\) is transformed according to \(s (p - c) + c\).

Parameters

scale	The scale parameter that is multiplied to the points/vertices of the geometry.
center	Scale center that is used to resize the geometry.

Implements open3d::geometry::Geometry3D.

◆ SegmentPlane()

std::tuple< Eigen::Vector4d, std::vector< size_t > > open3d::geometry::PointCloud::SegmentPlane	(	const double	distance_threshold = `0.01`,
		const int	ransac_n = `3`,
		const int	num_iterations = `100`,
		const double	probability = `0.99999999`
	)		const

Segment PointCloud plane using the RANSAC algorithm.

Parameters

distance_threshold	Max distance a point can be from the plane model, and still be considered an inlier.
ransac_n	Number of initial points to be considered inliers in each iteration.
num_iterations	Maximum number of iterations.
probability	Expected probability of finding the optimal plane.

Returns: Returns the plane model ax + by + cz + d = 0 and the indices of the plane inliers.

◆ SelectByIndex()

std::shared_ptr< PointCloud > open3d::geometry::PointCloud::SelectByIndex	(	const std::vector< size_t > &	indices,
		bool	invert = `false`
	)		const

Selects points from input pointcloud, with indices in indices, and returns a new point-cloud with selected points.

Parameters

indices	Indices of points to be selected.
invert	Set to `True` to invert the selection of indices.

◆ Transform()

PointCloud & open3d::geometry::PointCloud::Transform ( const Eigen::Matrix4d & transformation )

overridevirtual

Apply transformation (4x4 matrix) to the geometry coordinates.

Implements open3d::geometry::Geometry3D.

◆ Translate()

PointCloud & open3d::geometry::PointCloud::Translate	(	const Eigen::Vector3d &	translation,
		bool	relative = `true`
	)

overridevirtual

Apply translation to the geometry coordinates.

Parameters

translation	A 3D vector to transform the geometry.
relative	If `true`, the `translation` is directly applied to the geometry. Otherwise, the geometry center is moved to the `translation`.

Implements open3d::geometry::Geometry3D.

◆ UniformDownSample()

std::shared_ptr< PointCloud > open3d::geometry::PointCloud::UniformDownSample ( size_t every_k_points ) const

Function to downsample input pointcloud into output pointcloud uniformly.

The sample is performed in the order of the points with the 0-th point always chosen, not at random.

Parameters

every_k_points Sample rate, the selected point indices are [0, k, 2k, …].

◆ VoxelDownSample()

std::shared_ptr< PointCloud > open3d::geometry::PointCloud::VoxelDownSample ( double voxel_size ) const

Downsample input pointcloud with a voxel, and return a new point-cloud. Normals, covariances and colors are averaged if they exist.

Parameters

voxel_size Defines the resolution of the voxel grid, smaller value leads to denser output point cloud.

◆ VoxelDownSampleAndTrace()

std::tuple< std::shared_ptr< PointCloud >, Eigen::MatrixXi, std::vector< std::vector< int > > > open3d::geometry::PointCloud::VoxelDownSampleAndTrace	(	double	voxel_size,
		const Eigen::Vector3d &	min_bound,
		const Eigen::Vector3d &	max_bound,
		bool	approximate_class = `false`
	)		const

Function to downsample using geometry.PointCloud.VoxelDownSample.

Also records point cloud index before downsampling.

Parameters

voxel_size	Voxel size to downsample into.
min_bound	Minimum coordinate of voxel boundaries
max_bound	Maximum coordinate of voxel boundaries
approximate_class	Whether to approximate.

Field Documentation

◆ colors_

std::vector<Eigen::Vector3d> open3d::geometry::PointCloud::colors_

RGB colors of points.

◆ covariances_

std::vector<Eigen::Matrix3d> open3d::geometry::PointCloud::covariances_

Covariance Matrix for each point.

◆ normals_

std::vector<Eigen::Vector3d> open3d::geometry::PointCloud::normals_

Points normals.

◆ points_

std::vector<Eigen::Vector3d> open3d::geometry::PointCloud::points_

Points coordinates.

The documentation for this class was generated from the following files:

/home/runner/work/Open3D/Open3D/cpp/open3d/geometry/PointCloud.h (252c867 (Sun May 5 05:39:34 2024 +0000))
/home/runner/work/Open3D/Open3D/cpp/open3d/geometry/EstimateNormals.cpp (252c867 (Sun May 5 05:39:34 2024 +0000))
/home/runner/work/Open3D/Open3D/cpp/open3d/geometry/PointCloud.cpp (252c867 (Sun May 5 05:39:34 2024 +0000))
/home/runner/work/Open3D/Open3D/cpp/open3d/geometry/PointCloudCluster.cpp (252c867 (Sun May 5 05:39:34 2024 +0000))
/home/runner/work/Open3D/Open3D/cpp/open3d/geometry/PointCloudFactory.cpp (252c867 (Sun May 5 05:39:34 2024 +0000))
/home/runner/work/Open3D/Open3D/cpp/open3d/geometry/PointCloudPlanarPatchDetection.cpp (252c867 (Sun May 5 05:39:34 2024 +0000))
/home/runner/work/Open3D/Open3D/cpp/open3d/geometry/PointCloudSegmentation.cpp (252c867 (Sun May 5 05:39:34 2024 +0000))

Public Member Functions

Static Public Member Functions

Data Fields

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ PointCloud() [1/2]

◆ PointCloud() [2/2]

◆ ~PointCloud()

Member Function Documentation

◆ Clear()

◆ ClusterDBSCAN()

◆ ComputeConvexHull()

◆ ComputeMahalanobisDistance()

◆ ComputeMeanAndCovariance()

◆ ComputeNearestNeighborDistance()

◆ ComputePointCloudDistance()

◆ CreateFromDepthImage()

◆ CreateFromRGBDImage()

◆ CreateFromVoxelGrid()

◆ Crop() [1/2]

◆ Crop() [2/2]

◆ DetectPlanarPatches()

◆ EstimateCovariances()

◆ EstimateNormals()

◆ EstimatePerPointCovariances()

◆ FarthestPointDownSample()

◆ GetAxisAlignedBoundingBox()

◆ GetCenter()

◆ GetMaxBound()

◆ GetMinBound()

◆ GetMinimalOrientedBoundingBox()

◆ GetOrientedBoundingBox()

◆ HasColors()

◆ HasCovariances()

◆ HasNormals()

◆ HasPoints()

◆ HiddenPointRemoval()

◆ IsEmpty()

◆ NormalizeNormals()

◆ operator+()

◆ operator+=()

◆ OrientNormalsConsistentTangentPlane()

◆ OrientNormalsToAlignWithDirection()

◆ OrientNormalsTowardsCameraLocation()

◆ PaintUniformColor()

◆ RandomDownSample()

◆ RemoveDuplicatedPoints()

◆ RemoveNonFinitePoints()

◆ RemoveRadiusOutliers()

◆ RemoveStatisticalOutliers()

◆ Rotate()

◆ Scale()

◆ SegmentPlane()

◆ SelectByIndex()

◆ Transform()

◆ Translate()

◆ UniformDownSample()

◆ VoxelDownSample()

◆ VoxelDownSampleAndTrace()

Field Documentation

◆ colors_

◆ covariances_

◆ normals_

◆ points_