Point Cloud Library (PCL)
1.3.1
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Software License Agreement (BSD License) More...
Namespaces | |
namespace | apps |
namespace | ComparisonOps |
namespace | console |
namespace | detail |
namespace | distances |
namespace | fields |
namespace | geometry |
namespace | io |
namespace | octree |
namespace | registration |
namespace | search |
namespace | surface |
namespace | traits |
namespace | utils |
namespace | visualization |
Classes | |
class | NNClassification |
Nearest neighbor search based classification of PCL point type features. More... | |
class | VFHClassifierNN |
Utility class for nearest neighbor search based classification of VFH features. More... | |
class | BivariatePolynomialT |
This represents a bivariate polynomial and provides some functionality for it. More... | |
struct | NdCentroidFunctor |
Helper functor structure for n-D centroid estimation. More... | |
struct | NdConcatenateFunctor |
Helper functor structure for concatenate. More... | |
class | PCA |
Principal Component analysis (PCA) class. More... | |
class | PiecewiseLinearFunction |
This provides functionalities to efficiently return values for piecewise linear function. More... | |
struct | PointCorrespondence |
Representation of a (possible) correspondence between two points in two different coordinate frames (e.g. More... | |
struct | PointCorrespondence3D |
Representation of a (possible) correspondence between two 3D points in two different coordinate frames (e.g. More... | |
struct | PointCorrespondence6D |
Representation of a (possible) correspondence between two points (e.g. More... | |
class | PolynomialCalculationsT |
This provides some functionality for polynomials, like finding roots or approximating bivariate polynomials. More... | |
class | PosesFromMatches |
calculate 3D transformation based on point correspondencdes More... | |
class | Synchronizer |
/brief This template class synchronizes two data streams of different types. More... | |
class | StopWatch |
Simple stopwatch. More... | |
class | ScopeTime |
Class to measure the time spent in a scope. More... | |
class | TimeTrigger |
timer class that invokes registered callback methods periodically. More... | |
class | TransformationFromCorrespondences |
Calculates a transformation based on corresponding 3D points. More... | |
class | VectorAverage |
Calculates the weighted average and the covariance matrix. More... | |
struct | Correspondence |
Correspondence represents a match between two entities (e.g., points, descriptors, etc). More... | |
class | PCLException |
A base class for all pcl exceptions which inherits from std::runtime_error. More... | |
class | InvalidConversionException |
An exception that is thrown when a PointCloud2 message cannot be converted into a PCL type. More... | |
class | IsNotDenseException |
An exception that is thrown when a PointCloud is not dense but is attemped to be used as dense. More... | |
class | InvalidSACModelTypeException |
An exception that is thrown when a sample consensus model doesn't have the correct number of samples defined in model_types.h. More... | |
class | IOException |
An exception that is thrown during an IO error (typical read/write errors) More... | |
struct | _PointXYZ |
struct | PointXYZ |
A point structure representing Euclidean xyz coordinates. More... | |
struct | RGB |
A structure representing RGB color information. More... | |
struct | PointXYZI |
A point structure representing Euclidean xyz coordinates, and the intensity value. More... | |
struct | PointXYZL |
struct | _PointXYZRGBA |
A point structure representing Euclidean xyz coordinates, and the RGBA color. More... | |
struct | PointXYZRGBA |
struct | _PointXYZRGB |
struct | _PointXYZRGBL |
struct | PointXYZRGB |
A point structure representing Euclidean xyz coordinates, and the RGB color. More... | |
struct | PointXYZRGBL |
struct | _PointXYZHSV |
struct | PointXYZHSV |
struct | PointXY |
A 2D point structure representing Euclidean xy coordinates. More... | |
struct | InterestPoint |
A point structure representing an interest point with Euclidean xyz coordinates, and an interest value. More... | |
struct | Normal |
A point structure representing normal coordinates and the surface curvature estimate. More... | |
struct | PointNormal |
A point structure representing Euclidean xyz coordinates, together with normal coordinates and the surface curvature estimate. More... | |
struct | _PointXYZRGBNormal |
A point structure representing Euclidean xyz coordinates, and the RGB color, together with normal coordinates and the surface curvature estimate. More... | |
struct | PointXYZRGBNormal |
struct | PointXYZINormal |
A point structure representing Euclidean xyz coordinates, intensity, together with normal coordinates and the surface curvature estimate. More... | |
struct | PointWithRange |
A point structure representing Euclidean xyz coordinates, padded with an extra range float. More... | |
struct | _PointWithViewpoint |
struct | PointWithViewpoint |
A point structure representing Euclidean xyz coordinates together with the viewpoint from which it was seen. More... | |
struct | MomentInvariants |
A point structure representing the three moment invariants. More... | |
struct | PrincipalRadiiRSD |
A point structure representing the minimum and maximum surface radii (in meters) computed using RSD. More... | |
struct | Boundary |
A point structure representing a description of whether a point is lying on a surface boundary or not. More... | |
struct | PrincipalCurvatures |
A point structure representing the principal curvatures and their magnitudes. More... | |
struct | PFHSignature125 |
A point structure representing the Point Feature Histogram (PFH). More... | |
struct | PFHRGBSignature250 |
A point structure representing the Point Feature Histogram with colors (PFHRGB). More... | |
struct | PPFSignature |
A point structure for storing the Point Pair Feature (PPF) values. More... | |
struct | PPFRGBSignature |
A point structure for storing the Point Pair Color Feature (PPFRGB) values. More... | |
struct | NormalBasedSignature12 |
A point structure representing the Normal Based Signature for a feature matrix of 4-by-3. More... | |
struct | SHOT |
A point structure representing the generic Signature of Histograms of OrienTations (SHOT). More... | |
struct | FPFHSignature33 |
A point structure representing the Signature of Histograms of OrienTations (SHOT). More... | |
struct | VFHSignature308 |
A point structure representing the Viewpoint Feature Histogram (VFH). More... | |
struct | Narf36 |
A point structure representing the Narf descriptor. More... | |
struct | BorderDescription |
A structure to store if a point in a range image lies on a border between an obstacle and the background. More... | |
struct | IntensityGradient |
A point structure representing the intensity gradient of an XYZI point cloud. More... | |
struct | Histogram |
A point structure representing an N-D histogram. More... | |
struct | PointWithScale |
A point structure representing a 3-D position and scale. More... | |
struct | PointSurfel |
A surfel, that is, a point structure representing Euclidean xyz coordinates, together with normal coordinates, a RGBA color, a radius, a confidence value and the surface curvature estimate. More... | |
struct | ModelCoefficients |
class | PCLBase |
PCL base class. More... | |
class | PCLBase< sensor_msgs::PointCloud2 > |
class | PointCloud |
PointCloud represents a templated PointCloud implementation. More... | |
class | PointRepresentation |
PointRepresentation provides a set of methods for converting a point structs/object into an n-dimensional vector. More... | |
class | DefaultPointRepresentation |
DefaultPointRepresentation extends PointRepresentation to define default behavior for common point types. More... | |
class | DefaultFeatureRepresentation |
DefaulFeatureRepresentation extends PointRepresentation and is intended to be used when defining the default behavior for feature descriptor types (i.e., copy each element of each field into a float array). More... | |
class | DefaultPointRepresentation< PointXYZ > |
class | DefaultPointRepresentation< PointXYZI > |
class | DefaultPointRepresentation< PointNormal > |
class | DefaultPointRepresentation< PFHSignature125 > |
class | DefaultPointRepresentation< PFHRGBSignature250 > |
class | DefaultPointRepresentation< PPFSignature > |
class | DefaultPointRepresentation< FPFHSignature33 > |
class | DefaultPointRepresentation< VFHSignature308 > |
class | DefaultPointRepresentation< NormalBasedSignature12 > |
class | DefaultPointRepresentation< SHOT > |
class | CustomPointRepresentation |
CustomPointRepresentation extends PointRepresentation to allow for sub-part selection on the point. More... | |
struct | PointIndices |
struct | PolygonMesh |
struct | for_each_type_impl |
struct | for_each_type_impl< false > |
struct | intersect |
struct | TexMaterial |
struct | TextureMesh |
struct | Vertices |
Describes a set of vertices in a polygon mesh, by basically storing an array of indices. More... | |
class | ShapeContext3DEstimation |
Class ShapeContext3DEstimation implements the 3D shape context descriptor as described here. More... | |
class | BoundaryEstimation |
BoundaryEstimation estimates whether a set of points is lying on surface boundaries using an angle criterion. More... | |
class | CVFHEstimation |
CVFHEstimation estimates the Clustered Viewpoint Feature Histogram (CVFH) descriptor for a given point cloud dataset containing points and normals. More... | |
class | Feature |
Feature represents the base feature class. More... | |
class | FeatureFromNormals |
class | FPFHEstimation |
FPFHEstimation estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud dataset containing points and normals. More... | |
class | FPFHEstimationOMP |
FPFHEstimationOMP estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud dataset containing points and normals, in parallel, using the OpenMP standard. More... | |
struct | IntegralImageTypeTraits |
struct | IntegralImageTypeTraits< float > |
struct | IntegralImageTypeTraits< char > |
struct | IntegralImageTypeTraits< short > |
struct | IntegralImageTypeTraits< unsigned short > |
struct | IntegralImageTypeTraits< unsigned char > |
struct | IntegralImageTypeTraits< int > |
struct | IntegralImageTypeTraits< unsigned int > |
class | IntegralImage2Dim |
Determines an integral image representation for a given organized data array. More... | |
class | IntegralImage2D |
Generic implementation for creating 2D integral images (including second order integral images). More... | |
class | IntegralImageNormalEstimation |
Surface normal estimation on dense data using integral images. More... | |
class | IntensityGradientEstimation |
IntensityGradientEstimation estimates the intensity gradient for a point cloud that contains position and intensity values. More... | |
class | IntensitySpinEstimation |
IntensitySpinEstimation estimates the intensity-domain spin image descriptors for a given point cloud dataset containing points and intensity. More... | |
class | MomentInvariantsEstimation |
MomentInvariantsEstimation estimates the 3 moment invariants (j1, j2, j3) at each 3D point. More... | |
class | MultiscaleFeaturePersistence |
Generic class for extracting the persistent features from an input point cloud It can be given any Feature estimator instance and will compute the features of the input over a multiscale representation of the cloud and output the unique ones over those scales. More... | |
class | Narf |
NARF (Normal Aligned Radial Features) is a point feature descriptor type for 3D data. More... | |
class | NarfDescriptor |
Computes NARF feature descriptors for points in a range image More... | |
class | NormalEstimation |
NormalEstimation estimates local surface properties at each 3D point, such as surface normals and curvatures. More... | |
class | NormalEstimationOMP |
NormalEstimationOMP estimates local surface properties at each 3D point, such as surface normals and curvatures, in parallel, using the OpenMP standard. More... | |
class | NormalBasedSignatureEstimation |
Normal-based feature signature estimation class. More... | |
class | PFHEstimation |
PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals. More... | |
class | PFHRGBEstimation |
class | PPFEstimation |
Class that calculates the "surflet" features for each pair in the given pointcloud. More... | |
class | PPFRGBEstimation |
class | PPFRGBRegionEstimation |
class | PrincipalCurvaturesEstimation |
PrincipalCurvaturesEstimation estimates the directions (eigenvectors) and magnitudes (eigenvalues) of principal surface curvatures for a given point cloud dataset containing points and normals. More... | |
class | RangeImageBorderExtractor |
Extract obstacle borders from range images, meaning positions where there is a transition from foreground to background. More... | |
class | RIFTEstimation |
RIFTEstimation estimates the Rotation Invariant Feature Transform descriptors for a given point cloud dataset containing points and intensity. More... | |
class | RSDEstimation |
RSDEstimation estimates the Radius-based Surface Descriptor (minimal and maximal radius of the local surface's curves) for a given point cloud dataset containing points and normals. More... | |
class | SHOTEstimationBase |
SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals. More... | |
class | SHOTEstimation |
SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals. More... | |
class | SHOTEstimation< pcl::PointXYZRGBA, PointNT, PointOutT > |
SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals. More... | |
class | SHOTEstimationOMP |
SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals, in parallel, using the OpenMP standard. More... | |
class | SHOTEstimationOMP< pcl::PointXYZRGBA, PointNT, PointOutT > |
class | SpinImageEstimation |
Estimates spin-image descriptors in the given input points. More... | |
class | StatisticalMultiscaleInterestRegionExtraction |
Class for extracting interest regions from unstructured point clouds, based on a multi scale statistical approach. More... | |
class | UniqueShapeContext |
Class UniqueShapeContext implements the unique shape descriptor described here. More... | |
class | VFHEstimation |
VFHEstimation estimates the Viewpoint Feature Histogram (VFH) descriptor for a given point cloud dataset containing points and normals. More... | |
struct | he |
struct | xNdCopyEigenPointFunctor |
Helper functor structure for copying data between an Eigen::VectorXf and a PointT. More... | |
struct | xNdCopyPointEigenFunctor |
Helper functor structure for copying data between an Eigen::VectorXf and a PointT. More... | |
class | ApproximateVoxelGrid |
ApproximateVoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More... | |
class | BilateralFilter |
A bilateral filter implementation for point cloud data. More... | |
class | ColorFilter |
class | ColorFilter< sensor_msgs::PointCloud2 > |
class | PointDataAtOffset |
A datatype that enables type-correct comparisons. More... | |
class | ComparisonBase |
The (abstract) base class for the comparison object. More... | |
class | FieldComparison |
The field-based specialization of the comparison object. More... | |
class | PackedRGBComparison |
A packed rgb specialization of the comparison object. More... | |
class | PackedHSIComparison |
A packed HSI specialization of the comparison object. More... | |
class | ConditionBase |
Base condition class. More... | |
class | ConditionAnd |
AND condition. More... | |
class | ConditionOr |
OR condition. More... | |
class | ConditionalRemoval |
ConditionalRemoval filters data that satisfies certain conditions. More... | |
class | CropBox |
More... | |
class | CropBox< sensor_msgs::PointCloud2 > |
More... | |
class | ExtractIndices |
ExtractIndices extracts a set of indices from a PointCloud as a separate PointCloud. More... | |
class | ExtractIndices< sensor_msgs::PointCloud2 > |
ExtractIndices extracts a set of indices from a PointCloud as a separate PointCloud. More... | |
class | Filter |
Filter represents the base filter class. More... | |
class | Filter< sensor_msgs::PointCloud2 > |
Filter represents the base filter class. More... | |
class | FilterIndices |
Filter represents the base filter class. More... | |
class | FilterIndices< sensor_msgs::PointCloud2 > |
FilterIndices represents the base filter with indices class. More... | |
class | PassThrough |
PassThrough uses the base Filter class methods to pass through all data that satisfies the user given constraints. More... | |
class | PassThrough< sensor_msgs::PointCloud2 > |
PassThrough uses the base Filter class methods to pass through all data that satisfies the user given constraints. More... | |
class | ProjectInliers |
ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud. More... | |
class | ProjectInliers< sensor_msgs::PointCloud2 > |
ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud. More... | |
class | RadiusOutlierRemoval |
RadiusOutlierRemoval is a simple filter that removes outliers if the number of neighbors in a certain search radius is smaller than a given K. More... | |
class | RadiusOutlierRemoval< sensor_msgs::PointCloud2 > |
RadiusOutlierRemoval is a simple filter that removes outliers if the number of neighbors in a certain search radius is smaller than a given K. More... | |
class | RandomSample |
RandomSample applies a random sampling with uniform probability. More... | |
class | RandomSample< sensor_msgs::PointCloud2 > |
RandomSample applies a random sampling with uniform probability. More... | |
class | StatisticalOutlierRemoval |
StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. More... | |
class | StatisticalOutlierRemoval< sensor_msgs::PointCloud2 > |
StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. More... | |
struct | NdCopyEigenPointFunctor |
Helper functor structure for copying data between an Eigen::VectorXf and a PointT. More... | |
struct | NdCopyPointEigenFunctor |
Helper functor structure for copying data between an Eigen::VectorXf and a PointT. More... | |
class | VoxelGrid |
VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More... | |
class | VoxelGrid< sensor_msgs::PointCloud2 > |
VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More... | |
class | AdaptiveRangeCoder |
AdaptiveRangeCoder compression class More... | |
class | StaticRangeCoder |
StaticRangeCoder compression class More... | |
class | FileReader |
Point Cloud Data (FILE) file format reader interface. More... | |
class | FileWriter |
Point Cloud Data (FILE) file format writer. More... | |
class | PCDReader |
Point Cloud Data (PCD) file format reader. More... | |
class | PCDWriter |
Point Cloud Data (PCD) file format writer. More... | |
class | PCLIOException |
/brief /ingroup io More... | |
class | PLYReader |
Point Cloud Data (PLY) file format reader. More... | |
class | PLYWriter |
Point Cloud Data (PLY) file format writer. More... | |
class | KdTree |
KdTree represents the base spatial locator class for nearest neighbor estimation. More... | |
class | KdTreeFLANN |
KdTreeFLANN is a generic type of 3D spatial locator using kD-tree structures. More... | |
class | HarrisKeypoint3D |
class | Keypoint |
Keypoint represents the base class for key points. More... | |
class | NarfKeypoint |
NARF (Normal Aligned Radial Feature) keypoints. More... | |
struct | SIFTKeypointFieldSelector |
struct | SIFTKeypointFieldSelector< PointNormal > |
struct | SIFTKeypointFieldSelector< PointXYZRGB > |
class | SIFTKeypoint |
SIFTKeypoint detects the Scale Invariant Feature Transform keypoints for a given point cloud dataset containing points and intensity. More... | |
class | SmoothedSurfacesKeypoint |
Based on the paper: Xinju Li and Igor Guskov Multi-scale features for approximate alignment of point-based surfaces Proceedings of the third Eurographics symposium on Geometry processing July 2005, Vienna, Austria. More... | |
class | UniformSampling |
UniformSampling assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More... | |
class | RangeImage |
RangeImage is derived from pcl/PointCloud and provides functionalities with focus on situations where a 3D scene was captured from a specific view point. More... | |
class | RangeImagePlanar |
RangeImagePlanar is derived from the original range image and differs from it because it's not a spherical projection, but using a projection plane (as normal cameras do), therefore being better applicable for range sensors that already provide a range image by themselves (stereo cameras, ToF-cameras), so that a conversion to point cloud and then to a spherical range image becomes unnecessary. More... | |
class | GeneralizedIterativeClosestPoint |
GeneralizedIterativeClosestPoint is an ICP variant that implements the generalized iterative closest point algorithm as described by Alex Segal et al. More... | |
class | SampleConsensusInitialAlignment |
SampleConsensusInitialAlignment is an implementation of the initial alignment algorithm described in section IV of "Fast Point Feature Histograms (FPFH) for 3D Registration," Rusu et al. More... | |
class | IterativeClosestPoint |
IterativeClosestPoint provides a base implementation of the Iterative Closest Point algorithm. More... | |
class | IterativeClosestPointNonLinear |
IterativeClosestPointNonLinear is an ICP variant that uses Levenberg-Marquardt optimization backend. More... | |
class | PPFHashMapSearch |
class | PPFRegistration |
Class that registers two point clouds based on their sets of PPFSignatures. More... | |
class | PyramidFeatureHistogram |
Class that compares two sets of features by using a multiscale representation of the features inside a pyramid. More... | |
class | Registration |
Registration represents the base registration class. More... | |
class | WarpPointRigid |
class | WarpPointRigid3D |
class | WarpPointRigid6D |
class | LeastMedianSquares |
LeastMedianSquares represents an implementation of the LMedS (Least Median of Squares) algorithm. More... | |
class | MaximumLikelihoodSampleConsensus |
MaximumLikelihoodSampleConsensus represents an implementation of the MLESAC (Maximum Likelihood Estimator SAmple Consensus) algorithm, as described in: "MLESAC: A new robust estimator with application to
estimating image geometry", P.H.S. More... | |
class | MEstimatorSampleConsensus |
MEstimatorSampleConsensus represents an implementation of the MSAC (M-estimator SAmple Consensus) algorithm, as described in: "MLESAC: A new robust estimator with application to estimating image geometry", P.H.S. More... | |
class | ProgressiveSampleConsensus |
RandomSampleConsensus represents an implementation of the RANSAC (RAndom SAmple Consensus) algorithm, as described in: "Matching with PROSAC – Progressive Sample Consensus", Chum, O. More... | |
class | RandomSampleConsensus |
RandomSampleConsensus represents an implementation of the RANSAC (RAndom SAmple Consensus) algorithm, as described in: "Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and
Automated Cartography", Martin A. More... | |
class | RandomizedMEstimatorSampleConsensus |
RandomizedMEstimatorSampleConsensus represents an implementation of the RMSAC (Randomized M-estimator SAmple Consensus) algorithm, which basically adds a Td,d test (see RandomizedRandomSampleConsensus) to an MSAC estimator (see MEstimatorSampleConsensus). More... | |
class | RandomizedRandomSampleConsensus |
RandomizedRandomSampleConsensus represents an implementation of the RRANSAC (Randomized RAndom SAmple Consensus), as described in "Randomized RANSAC with Td,d test", O. More... | |
class | SampleConsensus |
SampleConsensus represents the base class. More... | |
class | SampleConsensusModel |
SampleConsensusModel represents the base model class. More... | |
class | SampleConsensusModelFromNormals |
SampleConsensusModelFromNormals represents the base model class for models that require the use of surface normals for estimation. More... | |
struct | Functor |
Base functor all the models that need non linear optimization must define their own one and implement operator() (const Eigen::VectorXd& x, Eigen::VectorXd& fvec) or operator() (const Eigen::VectorXf& x, Eigen::VectorXf& fvec) dependening on the choosen _Scalar. More... | |
class | SampleConsensusModelCircle2D |
SampleConsensusModelCircle2D defines a model for 2D circle segmentation on the X-Y plane. More... | |
class | SampleConsensusModelCylinder |
SampleConsensusModelCylinder defines a model for 3D cylinder segmentation. More... | |
class | SampleConsensusModelLine |
SampleConsensusModelLine defines a model for 3D line segmentation. More... | |
class | SampleConsensusModelNormalParallelPlane |
SampleConsensusModelNormalParallelPlane defines a model for 3D plane segmentation using additional surface normal constraints. More... | |
class | SampleConsensusModelNormalPlane |
SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface normal constraints. More... | |
class | SampleConsensusModelParallelLine |
SampleConsensusModelParallelLine defines a model for 3D line segmentation using additional angular constraints. More... | |
class | SampleConsensusModelParallelPlane |
SampleConsensusModelParallelPlane defines a model for 3D plane segmentation using additional angular constraints. More... | |
class | SampleConsensusModelPerpendicularPlane |
SampleConsensusModelPerpendicularPlane defines a model for 3D plane segmentation using additional angular constraints. More... | |
class | SampleConsensusModelPlane |
SampleConsensusModelPlane defines a model for 3D plane segmentation. More... | |
class | SampleConsensusModelRegistration |
SampleConsensusModelRegistration defines a model for Point-To-Point registration outlier rejection. More... | |
class | SampleConsensusModelSphere |
SampleConsensusModelSphere defines a model for 3D sphere segmentation. More... | |
class | SampleConsensusModelStick |
SampleConsensusModelStick defines a model for 3D stick segmentation. More... | |
class | EuclideanClusterExtraction |
EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense. More... | |
class | LabeledEuclideanClusterExtraction |
LabeledEuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense, with label info. More... | |
class | ExtractPolygonalPrismData |
ExtractPolygonalPrismData uses a set of point indices that represent a planar model, and together with a given height, generates a 3D polygonal prism. More... | |
class | SACSegmentation |
SACSegmentation represents the Nodelet segmentation class for Sample Consensus methods and models, in the sense that it just creates a Nodelet wrapper for generic-purpose SAC-based segmentation. More... | |
class | SACSegmentationFromNormals |
SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods and models that require the use of surface normals for estimation. More... | |
class | SegmentDifferences |
SegmentDifferences obtains the difference between two spatially aligned point clouds and returns the difference between them for a maximum given distance threshold. More... | |
class | EarClipping |
The ear clipping triangulation algorithm. More... | |
struct | SearchPoint |
class | GreedyProjectionTriangulation |
GreedyProjectionTriangulation is an implementation of a greedy triangulation algorithm for 3D points based on local 2D projections. More... | |
class | GridProjection |
Grid projection surface reconstruction method. More... | |
class | MarchingCubes |
The marching cubes surface reconstruction algorithm. More... | |
class | MarchingCubesGreedy |
The marching cubes surface reconstruction algorithm, using a "greedy" voxelization algorithm. More... | |
class | MarchingCubesGreedyDot |
The marching cubes surface reconstruction algorithm, using a "greedy" voxelization algorithm combined with a dot product, to remove the double surface effect. More... | |
class | MovingLeastSquares |
MovingLeastSquares represent an implementation of the MLS (Moving Least Squares) algorithm for data smoothing and improved normal estimation. More... | |
class | OrganizedFastMesh |
Simple triangulation/surface reconstruction for organized point clouds. More... | |
class | SurfaceReconstruction |
SurfaceReconstruction represents the base surface reconstruction class. More... | |
class | SurfelSmoothing |
class | TextureMapping |
The texture mapping algorithm. More... | |
class | RegistrationVisualizer |
RegistrationVisualizer represents the base class for rendering the intermediate positions ocupied by the source point cloud during it's registration to the target point cloud. More... | |
Typedefs | |
typedef BivariatePolynomialT < double > | BivariatePolynomiald |
typedef BivariatePolynomialT < float > | BivariatePolynomial |
typedef std::vector < PointCorrespondence3D, Eigen::aligned_allocator < PointCorrespondence3D > > | PointCorrespondences3DVector |
typedef std::vector < PointCorrespondence6D, Eigen::aligned_allocator < PointCorrespondence6D > > | PointCorrespondences6DVector |
typedef PolynomialCalculationsT < double > | PolynomialCalculationsd |
typedef PolynomialCalculationsT< float > | PolynomialCalculations |
typedef VectorAverage< float, 2 > | VectorAverage2f |
typedef VectorAverage< float, 3 > | VectorAverage3f |
typedef VectorAverage< float, 4 > | VectorAverage4f |
typedef std::vector < pcl::Correspondence, Eigen::aligned_allocator < pcl::Correspondence > > | Correspondences |
typedef boost::shared_ptr < Correspondences > | CorrespondencesPtr |
typedef boost::shared_ptr < const Correspondences > | CorrespondencesConstPtr |
typedef Eigen::Map < Eigen::Array3f > | Array3fMap |
typedef const Eigen::Map < const Eigen::Array3f > | Array3fMapConst |
typedef Eigen::Map < Eigen::Array4f, Eigen::Aligned > | Array4fMap |
typedef const Eigen::Map < const Eigen::Array4f, Eigen::Aligned > | Array4fMapConst |
typedef Eigen::Map < Eigen::Vector3f > | Vector3fMap |
typedef const Eigen::Map < const Eigen::Vector3f > | Vector3fMapConst |
typedef Eigen::Map < Eigen::Vector4f, Eigen::Aligned > | Vector4fMap |
typedef const Eigen::Map < const Eigen::Vector4f, Eigen::Aligned > | Vector4fMapConst |
typedef boost::shared_ptr < ::pcl::ModelCoefficients > | ModelCoefficientsPtr |
typedef boost::shared_ptr < ::pcl::ModelCoefficients const > | ModelCoefficientsConstPtr |
typedef boost::shared_ptr < std::vector< int > > | IndicesPtr |
typedef boost::shared_ptr < const std::vector< int > > | IndicesConstPtr |
typedef std::vector < detail::FieldMapping > | MsgFieldMap |
typedef std::bitset< 32 > | BorderTraits |
Data type to store extended information about a transition from foreground to backgroundSpecification of the fields for BorderDescription::traits. | |
typedef boost::shared_ptr < ::pcl::PointIndices > | PointIndicesPtr |
typedef boost::shared_ptr < ::pcl::PointIndices const > | PointIndicesConstPtr |
typedef boost::shared_ptr < ::pcl::PolygonMesh > | PolygonMeshPtr |
typedef boost::shared_ptr < ::pcl::PolygonMesh const > | PolygonMeshConstPtr |
typedef boost::shared_ptr < pcl::TextureMesh > | TextureMeshPtr |
typedef boost::shared_ptr < pcl::TextureMesh const > | TextureMeshConstPtr |
typedef boost::shared_ptr < Vertices > | VerticesPtr |
typedef boost::shared_ptr < Vertices const > | VerticesConstPtr |
Enumerations | |
enum | NormType { L1, L2_SQR, L2, LINF, JM, B, SUBLINEAR, CS, DIV, PF, K, KL, HIK } |
Enum that defines all the types of norms available. More... | |
enum | BorderTrait { BORDER_TRAIT__OBSTACLE_BORDER, BORDER_TRAIT__SHADOW_BORDER, BORDER_TRAIT__VEIL_POINT, BORDER_TRAIT__SHADOW_BORDER_TOP, BORDER_TRAIT__SHADOW_BORDER_RIGHT, BORDER_TRAIT__SHADOW_BORDER_BOTTOM, BORDER_TRAIT__SHADOW_BORDER_LEFT, BORDER_TRAIT__OBSTACLE_BORDER_TOP, BORDER_TRAIT__OBSTACLE_BORDER_RIGHT, BORDER_TRAIT__OBSTACLE_BORDER_BOTTOM, BORDER_TRAIT__OBSTACLE_BORDER_LEFT, BORDER_TRAIT__VEIL_POINT_TOP, BORDER_TRAIT__VEIL_POINT_RIGHT, BORDER_TRAIT__VEIL_POINT_BOTTOM, BORDER_TRAIT__VEIL_POINT_LEFT } |
Specification of the fields for BorderDescription::traits. More... | |
enum | SacModel { SACMODEL_PLANE, SACMODEL_LINE, SACMODEL_CIRCLE2D, SACMODEL_CIRCLE3D, SACMODEL_SPHERE, SACMODEL_CYLINDER, SACMODEL_CONE, SACMODEL_TORUS, SACMODEL_PARALLEL_LINE, SACMODEL_PERPENDICULAR_PLANE, SACMODEL_PARALLEL_LINES, SACMODEL_NORMAL_PLANE, SACMODEL_REGISTRATION, SACMODEL_PARALLEL_PLANE, SACMODEL_NORMAL_PARALLEL_PLANE, SACMODEL_STICK } |
Functions | |
template<typename PointT > | |
pcl::PointCloud < pcl::VFHSignature308 >::Ptr | computeVFH (typename PointCloud< PointT >::ConstPtr cloud, double radius) |
Helper function to extract the VFH feature describing the given point cloud. | |
float | rad2deg (float alpha) |
Convert an angle from radians to degrees. | |
float | deg2rad (float alpha) |
Convert an angle from degrees to radians. | |
double | rad2deg (double alpha) |
Convert an angle from radians to degrees. | |
double | deg2rad (double alpha) |
Convert an angle from degrees to radians. | |
template<typename real > | |
real | normAngle (real alpha) |
Normalize an angle to (-PI, PI]. | |
template<typename real > | |
std::ostream & | operator<< (std::ostream &os, const BivariatePolynomialT< real > &p) |
template<typename PointT > | |
void | compute3DCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f ¢roid) |
Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector. | |
template<typename PointT > | |
void | compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Vector4f ¢roid) |
Compute the 3D (X-Y-Z) centroid of a set of points using their indices and return it as a 3D vector. | |
template<typename PointT > | |
void | compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Vector4f ¢roid) |
Compute the 3D (X-Y-Z) centroid of a set of points using their indices and return it as a 3D vector. | |
template<typename PointT > | |
void | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4f ¢roid, Eigen::Matrix3f &covariance_matrix) |
Compute the 3x3 covariance matrix of a given set of points. | |
template<typename PointT > | |
void | computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4f ¢roid, Eigen::Matrix3f &covariance_matrix) |
Compute normalized the 3x3 covariance matrix of a given set of points. | |
template<typename PointT > | |
void | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, const Eigen::Vector4f ¢roid, Eigen::Matrix3f &covariance_matrix) |
Compute the 3x3 covariance matrix of a given set of points using their indices. | |
template<typename PointT > | |
void | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4f ¢roid, Eigen::Matrix3f &covariance_matrix) |
Compute the 3x3 covariance matrix of a given set of points using their indices. | |
template<typename PointT > | |
void | computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, const Eigen::Vector4f ¢roid, Eigen::Matrix3f &covariance_matrix) |
Compute the normalized 3x3 covariance matrix of a given set of points using their indices. | |
template<typename PointT > | |
void | computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4f ¢roid, Eigen::Matrix3f &covariance_matrix) |
Compute the normalized 3x3 covariance matrix of a given set of points using their indices. | |
template<typename PointT > | |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Vector4f ¢roid, pcl::PointCloud< PointT > &cloud_out) |
Subtract a centroid from a point cloud and return the de-meaned representation. | |
template<typename PointT > | |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, const Eigen::Vector4f ¢roid, pcl::PointCloud< PointT > &cloud_out) |
Subtract a centroid from a point cloud and return the de-meaned representation. | |
template<typename PointT > | |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Vector4f ¢roid, Eigen::MatrixXf &cloud_out) |
Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. | |
template<typename PointT > | |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, const Eigen::Vector4f ¢roid, Eigen::MatrixXf &cloud_out) |
Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. | |
template<typename PointT > | |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Vector4f ¢roid, Eigen::MatrixXf &cloud_out) |
Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. | |
template<typename PointT > | |
void | computeNDCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::VectorXf ¢roid) |
General, all purpose nD centroid estimation for a set of points using their indices. | |
template<typename PointT > | |
void | computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::VectorXf ¢roid) |
General, all purpose nD centroid estimation for a set of points using their indices. | |
template<typename PointT > | |
void | computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::VectorXf ¢roid) |
General, all purpose nD centroid estimation for a set of points using their indices. | |
double | getAngle3D (const Eigen::Vector4f &v1, const Eigen::Vector4f &v2) |
Compute the smallest angle between two vectors in the [ 0, PI ) interval in 3D. | |
void | getMeanStd (const std::vector< float > &values, double &mean, double &stddev) |
Compute both the mean and the standard deviation of an array of values. | |
template<typename PointT > | |
void | getPointsInBox (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, std::vector< int > &indices) |
Get a set of points residing in a box given its bounds. | |
template<typename PointT > | |
void | getMaxDistance (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4f &pivot_pt, Eigen::Vector4f &max_pt) |
Get the point at maximum distance from a given point and a given pointcloud. | |
template<typename PointT > | |
void | getMaxDistance (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, const Eigen::Vector4f &pivot_pt, Eigen::Vector4f &max_pt) |
Get the point at maximum distance from a given point and a given pointcloud. | |
template<typename PointT > | |
void | getMinMax3D (const pcl::PointCloud< PointT > &cloud, PointT &min_pt, PointT &max_pt) |
Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. | |
template<typename PointT > | |
void | getMinMax3D (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt) |
Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. | |
template<typename PointT > | |
void | getMinMax3D (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt) |
Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. | |
template<typename PointT > | |
void | getMinMax3D (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt) |
Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. | |
template<typename PointT > | |
double | getCircumcircleRadius (const PointT &pa, const PointT &pb, const PointT &pc) |
Compute the radius of a circumscribed circle for a triangle formed of three points pa, pb, and pc. | |
template<typename PointT > | |
void | getMinMax (const PointT &histogram, int len, float &min_p, float &max_p) |
Get the minimum and maximum values on a point histogram. | |
PCL_EXPORTS void | getMinMax (const sensor_msgs::PointCloud2 &cloud, int idx, const std::string &field_name, float &min_p, float &max_p) |
Get the minimum and maximum values on a point histogram. | |
PCL_EXPORTS void | getMeanStdDev (const std::vector< float > &values, double &mean, double &stddev) |
Compute both the mean and the standard deviation of an array of values. | |
PCL_EXPORTS void | lineToLineSegment (const Eigen::VectorXf &line_a, const Eigen::VectorXf &line_b, Eigen::Vector4f &pt1_seg, Eigen::Vector4f &pt2_seg) |
Get the shortest 3D segment between two 3D lines. | |
double | sqrPointToLineDistance (const Eigen::Vector4f &pt, const Eigen::Vector4f &line_pt, const Eigen::Vector4f &line_dir) |
Get the square distance from a point to a line (represented by a point and a direction) | |
double | sqrPointToLineDistance (const Eigen::Vector4f &pt, const Eigen::Vector4f &line_pt, const Eigen::Vector4f &line_dir, const double sqr_length) |
Get the square distance from a point to a line (represented by a point and a direction) | |
template<typename PointT > | |
double | getMaxSegment (const pcl::PointCloud< PointT > &cloud, PointT &pmin, PointT &pmax) |
Obtain the maximum segment in a given set of points, and return the minimum and maximum points. | |
template<typename PointT > | |
double | getMaxSegment (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, PointT &pmin, PointT &pmax) |
Obtain the maximum segment in a given set of points, and return the minimum and maximum points. | |
template<typename Scalar , typename Roots > | |
void | computeRoots2 (const Scalar &b, const Scalar &c, Roots &roots) |
template<typename Matrix , typename Roots > | |
void | computeRoots (const Matrix &m, Roots &roots) |
template<typename Matrix , typename Vector > | |
void | eigen33 (const Matrix &mat, Matrix &evecs, Vector &evals) |
void | getTransFromUnitVectorsZY (const Eigen::Vector3f &z_axis, const Eigen::Vector3f &y_direction, Eigen::Affine3f &transformation) |
Get the unique 3D rotation that will rotate z_axis into (0,0,1) and y_direction into a vector with x=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) | |
Eigen::Affine3f | getTransFromUnitVectorsZY (const Eigen::Vector3f &z_axis, const Eigen::Vector3f &y_direction) |
Get the unique 3D rotation that will rotate z_axis into (0,0,1) and y_direction into a vector with x=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) | |
void | getTransFromUnitVectorsXY (const Eigen::Vector3f &x_axis, const Eigen::Vector3f &y_direction, Eigen::Affine3f &transformation) |
Get the unique 3D rotation that will rotate x_axis into (1,0,0) and y_direction into a vector with z=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) | |
Eigen::Affine3f | getTransFromUnitVectorsXY (const Eigen::Vector3f &x_axis, const Eigen::Vector3f &y_direction) |
Get the unique 3D rotation that will rotate x_axis into (1,0,0) and y_direction into a vector with z=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) | |
void | getTransformationFromTwoUnitVectors (const Eigen::Vector3f &y_direction, const Eigen::Vector3f &z_axis, Eigen::Affine3f &transformation) |
Same as getTransFromUnitVectorsZY - for downwards compatibility. | |
Eigen::Affine3f | getTransformationFromTwoUnitVectors (const Eigen::Vector3f &y_direction, const Eigen::Vector3f &z_axis) |
Same as getTransFromUnitVectorsZY - for downwards compatibility. | |
void | getTransformationFromTwoUnitVectorsAndOrigin (const Eigen::Vector3f &y_direction, const Eigen::Vector3f &z_axis, const Eigen::Vector3f &origin, Eigen::Affine3f &transformation) |
Get the transformation that will translate orign to (0,0,0) and rotate z_axis into (0,0,1) and y_direction into a vector with x=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) | |
void | getEulerAngles (const Eigen::Affine3f &t, float &roll, float &pitch, float &yaw) |
Extract the Euler angles (XYZ-convention) from the given transformation. | |
void | getTranslationAndEulerAngles (const Eigen::Affine3f &t, float &x, float &y, float &z, float &roll, float &pitch, float &yaw) |
Extract x,y,z and the Euler angles (XYZ-convention) from the given transformation. | |
void | getTransformation (float x, float y, float z, float roll, float pitch, float yaw, Eigen::Affine3f &t) |
Create a transformation from the given translation and Euler angles (XYZ-convention) | |
Eigen::Affine3f | getTransformation (float x, float y, float z, float roll, float pitch, float yaw) |
Create a transformation from the given translation and Euler angles (XYZ-convention) | |
template<typename Derived > | |
void | saveBinary (const Eigen::MatrixBase< Derived > &matrix, std::ostream &file) |
Write a matrix to an output stream. | |
template<typename Derived > | |
void | loadBinary (Eigen::MatrixBase< Derived > &matrix, std::istream &file) |
Read a matrix from an input stream. | |
void | getAllPcdFilesInDirectory (const std::string &directory, std::vector< std::string > &file_names) |
Find all *.pcd files in the directory and return them sorted. | |
std::string | getFilenameWithoutPath (const std::string &input) |
Remove the path from the given string and return only the filename (the remaining string after the last '/') | |
std::string | getFilenameWithoutExtension (const std::string &input) |
Remove the extension from the given string and return only the filename (everything before the last '. | |
std::string | getFileExtension (const std::string &input) |
Get the file extension from the given string (the remaining string after the last '. | |
template<typename FloatVectorT > | |
float | selectNorm (FloatVectorT A, FloatVectorT B, int dim, NormType norm_type) |
Method that calculates any norm type available, based on the norm_type variable. | |
template<typename FloatVectorT > | |
float | L1_Norm (FloatVectorT A, FloatVectorT B, int dim) |
Compute the L1 norm of the vector between two points. | |
template<typename FloatVectorT > | |
float | L2_Norm_SQR (FloatVectorT A, FloatVectorT B, int dim) |
Compute the squared L2 norm of the vector between two points. | |
template<typename FloatVectorT > | |
float | L2_Norm (FloatVectorT A, FloatVectorT B, int dim) |
Compute the L2 norm of the vector between two points. | |
template<typename FloatVectorT > | |
float | Linf_Norm (FloatVectorT A, FloatVectorT B, int dim) |
Compute the L-infinity norm of the vector between two points. | |
template<typename FloatVectorT > | |
float | JM_Norm (FloatVectorT A, FloatVectorT B, int dim) |
Compute the JM norm of the vector between two points. | |
template<typename FloatVectorT > | |
float | B_Norm (FloatVectorT A, FloatVectorT B, int dim) |
Compute the B norm of the vector between two points. | |
template<typename FloatVectorT > | |
float | Sublinear_Norm (FloatVectorT A, FloatVectorT B, int dim) |
Compute the sublinear norm of the vector between two points. | |
template<typename FloatVectorT > | |
float | CS_Norm (FloatVectorT A, FloatVectorT B, int dim) |
Compute the CS norm of the vector between two points. | |
template<typename FloatVectorT > | |
float | Div_Norm (FloatVectorT A, FloatVectorT B, int dim) |
Compute the div norm of the vector between two points. | |
template<typename FloatVectorT > | |
float | PF_Norm (FloatVectorT A, FloatVectorT B, int dim, float P1, float P2) |
Compute the PF norm of the vector between two points. | |
template<typename FloatVectorT > | |
float | K_Norm (FloatVectorT A, FloatVectorT B, int dim, float P1, float P2) |
Compute the K norm of the vector between two points. | |
template<typename FloatVectorT > | |
float | KL_Norm (FloatVectorT A, FloatVectorT B, int dim) |
Compute the KL between two discrete probability density functions. | |
template<typename FloatVectorT > | |
float | HIK_Norm (FloatVectorT A, FloatVectorT B, int dim) |
Compute the HIK norm of the vector between two points. | |
PCL_EXPORTS bool | lineWithLineIntersection (const Eigen::VectorXf &line_a, const Eigen::VectorXf &line_b, Eigen::Vector4f &point, double sqr_eps=1e-4) |
Get the intersection of a two 3D lines in space as a 3D point. | |
PCL_EXPORTS bool | lineWithLineIntersection (const pcl::ModelCoefficients &line_a, const pcl::ModelCoefficients &line_b, Eigen::Vector4f &point, double sqr_eps=1e-4) |
Get the intersection of a two 3D lines in space as a 3D point. | |
int | getFieldIndex (const sensor_msgs::PointCloud2 &cloud, const std::string &field_name) |
Get the index of a specified field (i.e., dimension/channel) | |
template<typename PointT > | |
int | getFieldIndex (const pcl::PointCloud< PointT > &cloud, const std::string &field_name, std::vector< sensor_msgs::PointField > &fields) |
Get the index of a specified field (i.e., dimension/channel) | |
template<typename PointT > | |
void | getFields (const pcl::PointCloud< PointT > &cloud, std::vector< sensor_msgs::PointField > &fields) |
Get the list of available fields (i.e., dimension/channel) | |
template<typename PointT > | |
std::string | getFieldsList (const pcl::PointCloud< PointT > &cloud) |
Get the list of all fields available in a given cloud. | |
std::string | getFieldsList (const sensor_msgs::PointCloud2 &cloud) |
Get the available point cloud fields as a space separated string. | |
int | getFieldSize (const int datatype) |
Obtains the size of a specific field data type in bytes. | |
PCL_EXPORTS void | getFieldsSizes (const std::vector< sensor_msgs::PointField > &fields, std::vector< int > &field_sizes) |
Obtain a vector with the sizes of all valid fields (e.g., not "_") | |
int | getFieldType (const int size, char type) |
Obtains the type of the PointField from a specific size and type. | |
char | getFieldType (const int type) |
Obtains the type of the PointField from a specific PointField as a char. | |
template<typename PointInT , typename PointOutT > | |
void | copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, pcl::PointCloud< PointOutT > &cloud_out) |
Copy all the fields from a given point cloud into a new point cloud. | |
PCL_EXPORTS bool | concatenatePointCloud (const sensor_msgs::PointCloud2 &cloud1, const sensor_msgs::PointCloud2 &cloud2, sensor_msgs::PointCloud2 &cloud_out) |
Concatenate two sensor_msgs::PointCloud2. | |
PCL_EXPORTS void | copyPointCloud (const sensor_msgs::PointCloud2 &cloud_in, const std::vector< int > &indices, sensor_msgs::PointCloud2 &cloud_out) |
Extract the indices of a given point cloud as a new point cloud. | |
template<typename PointT > | |
void | copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, pcl::PointCloud< PointT > &cloud_out) |
Extract the indices of a given point cloud as a new point cloud. | |
template<typename PointT > | |
void | copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int, Eigen::aligned_allocator< int > > &indices, pcl::PointCloud< PointT > &cloud_out) |
Extract the indices of a given point cloud as a new point cloud. | |
template<typename PointInT , typename PointOutT > | |
void | copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, const std::vector< int > &indices, pcl::PointCloud< PointOutT > &cloud_out) |
Extract the indices of a given point cloud as a new point cloud. | |
template<typename PointInT , typename PointOutT > | |
void | copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, const std::vector< int, Eigen::aligned_allocator< int > > &indices, pcl::PointCloud< PointOutT > &cloud_out) |
Extract the indices of a given point cloud as a new point cloud. | |
template<typename PointT > | |
void | copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, const PointIndices &indices, pcl::PointCloud< PointT > &cloud_out) |
Extract the indices of a given point cloud as a new point cloud. | |
template<typename PointInT , typename PointOutT > | |
void | copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, const PointIndices &indices, pcl::PointCloud< PointOutT > &cloud_out) |
Extract the indices of a given point cloud as a new point cloud. | |
template<typename PointT > | |
void | copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< pcl::PointIndices > &indices, pcl::PointCloud< PointT > &cloud_out) |
Extract the indices of a given point cloud as a new point cloud. | |
template<typename PointInT , typename PointOutT > | |
void | copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, const std::vector< pcl::PointIndices > &indices, pcl::PointCloud< PointOutT > &cloud_out) |
Extract the indices of a given point cloud as a new point cloud. | |
template<typename PointIn1T , typename PointIn2T , typename PointOutT > | |
void | concatenateFields (const pcl::PointCloud< PointIn1T > &cloud1_in, const pcl::PointCloud< PointIn2T > &cloud2_in, pcl::PointCloud< PointOutT > &cloud_out) |
Concatenate two datasets representing different fields. | |
PCL_EXPORTS bool | concatenateFields (const sensor_msgs::PointCloud2 &cloud1_in, const sensor_msgs::PointCloud2 &cloud2_in, sensor_msgs::PointCloud2 &cloud_out) |
Concatenate two datasets representing different fields. | |
PCL_EXPORTS bool | getPointCloudAsEigen (const sensor_msgs::PointCloud2 &in, Eigen::MatrixXf &out) |
Copy the XYZ dimensions of a sensor_msgs::PointCloud2 into Eigen format. | |
PCL_EXPORTS bool | getEigenAsPointCloud (Eigen::MatrixXf &in, sensor_msgs::PointCloud2 &out) |
Copy the XYZ dimensions from an Eigen MatrixXf into a sensor_msgs::PointCloud2 message. | |
bool | isBetterCorrespondence (const PointCorrespondence &pc1, const PointCorrespondence &pc2) |
Comparator to enable us to sort a vector of PointCorrespondences according to their scores using std::sort(begin(), end(), isBetterCorrespondence);. | |
double | getTime () |
template<typename PointT > | |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform) |
Apply an affine transform defined by an Eigen Transform. | |
template<typename PointT > | |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform) |
Apply an affine transform defined by an Eigen Transform. | |
template<typename PointT > | |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform) |
Transform a point cloud and rotate its normals using an Eigen transform. | |
template<typename PointT > | |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform) |
Apply an affine transform defined by an Eigen Transform. | |
template<typename PointT > | |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform) |
Transform a point cloud and rotate its normals using an Eigen transform. | |
template<typename PointT > | |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Vector3f &offset, const Eigen::Quaternionf &rotation) |
Apply a rigid transform defined by a 3D offset and a quaternion. | |
template<typename PointT > | |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Vector3f &offset, const Eigen::Quaternionf &rotation) |
Transform a point cloud and rotate its normals using an Eigen transform. | |
template<typename PointT > | |
PointT | transformPoint (const PointT &point, const Eigen::Affine3f &transform) |
Transform a point with members x,y,z. | |
std::ostream & | operator<< (std::ostream &os, const Correspondence &c) |
overloaded << operator | |
void | getRejectedQueryIndices (const pcl::Correspondences &correspondences_before, const pcl::Correspondences &correspondences_after, std::vector< int > &indices, bool presorting_required=true) |
Get the query points of correspondences that are present in one correspondence vector but not in the other, e.g., to compare correspondences before and after rejection. | |
std::ostream & | operator<< (std::ostream &os, const PointXYZ &p) |
std::ostream & | operator<< (std::ostream &os, const PointXYZI &p) |
std::ostream & | operator<< (std::ostream &os, const PointXYZL &p) |
std::ostream & | operator<< (std::ostream &os, const PointXYZRGBA &p) |
std::ostream & | operator<< (std::ostream &os, const PointXYZRGB &p) |
std::ostream & | operator<< (std::ostream &os, const PointXYZRGBL &p) |
std::ostream & | operator<< (std::ostream &os, const PointXYZHSV &p) |
std::ostream & | operator<< (std::ostream &os, const PointXY &p) |
std::ostream & | operator<< (std::ostream &os, const InterestPoint &p) |
std::ostream & | operator<< (std::ostream &os, const Normal &p) |
std::ostream & | operator<< (std::ostream &os, const PointNormal &p) |
std::ostream & | operator<< (std::ostream &os, const PointXYZRGBNormal &p) |
std::ostream & | operator<< (std::ostream &os, const PointXYZINormal &p) |
std::ostream & | operator<< (std::ostream &os, const PointWithRange &p) |
std::ostream & | operator<< (std::ostream &os, const PointWithViewpoint &p) |
std::ostream & | operator<< (std::ostream &os, const MomentInvariants &p) |
std::ostream & | operator<< (std::ostream &os, const PrincipalRadiiRSD &p) |
std::ostream & | operator<< (std::ostream &os, const Boundary &p) |
std::ostream & | operator<< (std::ostream &os, const PrincipalCurvatures &p) |
std::ostream & | operator<< (std::ostream &os, const PFHSignature125 &p) |
std::ostream & | operator<< (std::ostream &os, const PFHRGBSignature250 &p) |
std::ostream & | operator<< (std::ostream &os, const PPFSignature &p) |
std::ostream & | operator<< (std::ostream &os, const PPFRGBSignature &p) |
std::ostream & | operator<< (std::ostream &os, const NormalBasedSignature12 &p) |
std::ostream & | operator<< (std::ostream &os, const SHOT &p) |
std::ostream & | operator<< (std::ostream &os, const FPFHSignature33 &p) |
std::ostream & | operator<< (std::ostream &os, const VFHSignature308 &p) |
std::ostream & | operator<< (std::ostream &os, const Narf36 &p) |
std::ostream & | operator<< (std::ostream &os, const BorderDescription &p) |
std::ostream & | operator<< (std::ostream &os, const IntensityGradient &p) |
template<int N> | |
std::ostream & | operator<< (std::ostream &os, const Histogram< N > &p) |
std::ostream & | operator<< (std::ostream &os, const PointWithScale &p) |
std::ostream & | operator<< (std::ostream &os, const PointSurfel &p) |
template<typename PointType1 , typename PointType2 > | |
float | squaredEuclideanDistance (const PointType1 &p1, const PointType2 &p2) |
Calculate the squared euclidean distance between the two given points. | |
template<typename PointType1 , typename PointType2 > | |
float | euclideanDistance (const PointType1 &p1, const PointType2 &p2) |
Calculate the euclidean distance between the two given points. | |
template<typename PointType > | |
bool | hasValidXYZ (const PointType &p) |
Checks if x,y,z are finite numbers. | |
std::ostream & | operator<< (std::ostream &s, const ::pcl::ModelCoefficients &v) |
template<typename PointT > | |
std::ostream & | operator<< (std::ostream &s, const pcl::PointCloud< PointT > &p) |
void | PointXYZRGBtoXYZI (PointXYZRGB &in, PointXYZI &out) |
Convert a XYZRGB point type to a XYZI. | |
void | PointXYZRGBtoXYZHSV (PointXYZRGB &in, PointXYZHSV &out) |
Convert a XYZRGB point type to a XYZHSV. | |
void | PointXYZHSVtoXYZRGB (PointXYZHSV &in, PointXYZRGB &out) |
Convert a XYZHSV point type to a XYZRGB. | |
void | PointCloudXYZRGBtoXYZHSV (PointCloud< PointXYZRGB > &in, PointCloud< PointXYZHSV > &out) |
Convert a XYZRGB point cloud to a XYZHSV. | |
std::ostream & | operator<< (std::ostream &s, const ::pcl::PointIndices &v) |
std::ostream & | operator<< (std::ostream &s, const ::pcl::PolygonMesh &v) |
template<typename PointT > | |
void | createMapping (const std::vector< sensor_msgs::PointField > &msg_fields, MsgFieldMap &field_map) |
template<typename PointT > | |
void | fromROSMsg (const sensor_msgs::PointCloud2 &msg, pcl::PointCloud< PointT > &cloud, const MsgFieldMap &field_map) |
template<typename PointT > | |
void | fromROSMsg (const sensor_msgs::PointCloud2 &msg, pcl::PointCloud< PointT > &cloud) |
template<typename PointT > | |
void | toROSMsg (const pcl::PointCloud< PointT > &cloud, sensor_msgs::PointCloud2 &msg) |
template<typename CloudT > | |
void | toROSMsg (const CloudT &cloud, sensor_msgs::Image &msg) |
Copy the RGB fields of a PointCloud into sensor_msgs::Image format. | |
void | toROSMsg (const sensor_msgs::PointCloud2 &cloud, sensor_msgs::Image &msg) |
Copy the RGB fields of a PointCloud2 msg into sensor_msgs::Image format. | |
template<typename Sequence , typename F > | |
void | for_each_type (F f) |
std::ostream & | operator<< (std::ostream &s, const ::pcl::Vertices &v) |
void | solvePlaneParameters (const Eigen::Matrix3f &covariance_matrix, const Eigen::Vector4f &point, Eigen::Vector4f &plane_parameters, float &curvature) |
Solve the eigenvalues and eigenvectors of a given 3x3 covariance matrix, and estimate the least-squares plane normal and surface curvature. | |
void | solvePlaneParameters (const Eigen::Matrix3f &covariance_matrix, float &nx, float &ny, float &nz, float &curvature) |
Solve the eigenvalues and eigenvectors of a given 3x3 covariance matrix, and estimate the least-squares plane normal and surface curvature. | |
std::ostream & | operator<< (std::ostream &os, const RangeImageBorderExtractor::Parameters &p) |
template<typename PointT > | |
void | computePointNormal (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f &plane_parameters, float &curvature) |
Compute the Least-Squares plane fit for a given set of points, and return the estimated plane parameters together with the surface curvature. | |
template<typename PointT > | |
void | computePointNormal (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Vector4f &plane_parameters, float &curvature) |
Compute the Least-Squares plane fit for a given set of points, using their indices, and return the estimated plane parameters together with the surface curvature. | |
template<typename PointT > | |
void | flipNormalTowardsViewpoint (const PointT &point, float vp_x, float vp_y, float vp_z, Eigen::Vector4f &normal) |
Flip (in place) the estimated normal of a point towards a given viewpoint. | |
template<typename PointT > | |
void | flipNormalTowardsViewpoint (const PointT &point, float vp_x, float vp_y, float vp_z, float &nx, float &ny, float &nz) |
Flip (in place) the estimated normal of a point towards a given viewpoint. | |
PCL_EXPORTS bool | computePairFeatures (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, float &f1, float &f2, float &f3, float &f4) |
Compute the 4-tuple representation containing the three angles and one distance between two points represented by Cartesian coordinates and normals. | |
PCL_EXPORTS bool | computeRGBPairFeatures (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4i &colors1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, const Eigen::Vector4i &colors2, float &f1, float &f2, float &f3, float &f4, float &f5, float &f6, float &f7) |
PCL_EXPORTS bool | computePPFPairFeature (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, float &f1, float &f2, float &f3, float &f4) |
template<typename PointInT , typename PointNT , typename PointOutT > | |
void | computeRSD (const pcl::PointCloud< PointInT > &surface, const pcl::PointCloud< PointNT > &normals, const std::vector< int > &indices, double max_dist, int nr_subdiv, double plane_radius, PointOutT &radii) |
Estimate the Radius-based Surface Descriptor (RSD) for a given point based on its spatial neighborhood of 3D points with normals. | |
template<typename PointInT > | |
float | getLocalRF (const pcl::PointCloud< PointInT > &cloud, const double search_radius, const Eigen::Vector4f ¢ral_point, const std::vector< int > &indices, const std::vector< float > &dists, std::vector< Eigen::Vector4f, Eigen::aligned_allocator< Eigen::Vector4f > > &rf) |
Computes disambiguated local RF for a point index. | |
template<typename PointT > | |
void | removeNaNFromPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, std::vector< int > &index) |
Removes points with x, y, or z equal to NaN. | |
template<typename PointT > | |
void | removeNaNFromPointCloud (const pcl::PointCloud< PointT > &cloud_in, std::vector< int > &index) |
Removes points with x, y, or z equal to NaN. | |
PCL_EXPORTS void | getMinMax3D (const sensor_msgs::PointCloud2ConstPtr &cloud, int x_idx, int y_idx, int z_idx, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt) |
PCL_EXPORTS void | getMinMax3D (const sensor_msgs::PointCloud2ConstPtr &cloud, int x_idx, int y_idx, int z_idx, const std::string &distance_field_name, float min_distance, float max_distance, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, bool limit_negative=false) |
template<typename PointT > | |
void | getMinMax3D (const typename pcl::PointCloud< PointT >::ConstPtr &cloud, const std::string &distance_field_name, float min_distance, float max_distance, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, bool limit_negative=false) |
Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud, without considering points outside of a distance threshold from the laser origin. | |
template<typename Type > | |
void | copyValueString (const sensor_msgs::PointCloud2 &cloud, const unsigned int point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream) |
insers a value of type Type (uchar, char, uint, int, float, double, ...) into a stringstream. | |
template<> | |
void | copyValueString< int8_t > (const sensor_msgs::PointCloud2 &cloud, const unsigned int point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream) |
template<> | |
void | copyValueString< uint8_t > (const sensor_msgs::PointCloud2 &cloud, const unsigned int point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream) |
PCL_EXPORTS unsigned int | lzfCompress (const void *const in_data, unsigned int in_len, void *out_data, unsigned int out_len) |
Compress in_len bytes stored at the memory block starting at in_data and write the result to out_data, up to a maximum length of out_len bytes using Marc Lehmann's LZF algorithm. | |
PCL_EXPORTS unsigned int | lzfDecompress (const void *const in_data, unsigned int in_len, void *out_data, unsigned int out_len) |
Decompress data compressed with the lzfCompress function and stored at location in_data and length in_len. | |
void | throwPCLIOException (const char *function, const char *file, unsigned line, const char *format,...) |
/brief /ingroup io | |
template<typename PointT > | |
void | getApproximateIndices (const typename pcl::PointCloud< PointT >::Ptr &cloud_in, const typename pcl::PointCloud< PointT >::Ptr &cloud_ref, std::vector< int > &indices) |
Get a set of approximate indices for a given point cloud into a reference point cloud. | |
template<typename Point1T , typename Point2T > | |
void | getApproximateIndices (const typename pcl::PointCloud< Point1T >::Ptr &cloud_in, const typename pcl::PointCloud< Point2T >::Ptr &cloud_ref, std::vector< int > &indices) |
Get a set of approximate indices for a given point cloud into a reference point cloud. | |
std::ostream & | operator<< (std::ostream &os, const NarfKeypoint::Parameters &p) |
std::ostream & | operator<< (std::ostream &os, const RangeImage &r) |
/ingroup range_image | |
template<typename PointSource , typename PointTarget > | |
void | estimateRigidTransformationGICP (const pcl::PointCloud< PointSource > &cloud_src, const pcl::PointCloud< PointTarget > &cloud_tgt, Eigen::Matrix4f &transformation_matrix) |
Estimate a rigid rotation transformation between a source and a target point cloud using the transformation estimation step from the Generalized ICP alrogithm. | |
template<typename PointSource , typename PointTarget > | |
void | estimateRigidTransformationGICP (const pcl::PointCloud< PointSource > &cloud_src, const std::vector< int > &indices_src, const pcl::PointCloud< PointTarget > &cloud_tgt, Eigen::Matrix4f &transformation_matrix) |
Estimate a rigid rotation transformation between a source and a target point cloud using the transformation estimation step from the Generalized ICP alrogithm. | |
template<typename PointSource , typename PointTarget > | |
void | estimateRigidTransformationGICP (const pcl::PointCloud< PointSource > &cloud_src, const std::vector< int > &indices_src, const pcl::PointCloud< PointTarget > &cloud_tgt, const std::vector< int > &indices_tgt, Eigen::Matrix4f &transformation_matrix) |
Estimate a rigid rotation transformation between a source and a target point cloud using the transformation estimation step from the Generalized ICP alrogithm. | |
template<typename Point > | |
void | projectPoint (const Point &p, const Eigen::Vector4f &model_coefficients, Point &q) |
Project a point on a planar model given by a set of normalized coefficients. | |
template<typename Point > | |
double | pointToPlaneDistanceSigned (const Point &p, double a, double b, double c, double d) |
Get the distance from a point to a plane (signed) defined by ax+by+cz+d=0. | |
template<typename Point > | |
double | pointToPlaneDistanceSigned (const Point &p, const Eigen::Vector4f &plane_coefficients) |
Get the distance from a point to a plane (signed) defined by ax+by+cz+d=0. | |
template<typename Point > | |
double | pointToPlaneDistance (const Point &p, double a, double b, double c, double d) |
Get the distance from a point to a plane (unsigned) defined by ax+by+cz+d=0. | |
template<typename Point > | |
double | pointToPlaneDistance (const Point &p, const Eigen::Vector4f &plane_coefficients) |
Get the distance from a point to a plane (unsigned) defined by ax+by+cz+d=0. | |
template<typename PointT > | |
void | extractEuclideanClusters (const PointCloud< PointT > &cloud, const boost::shared_ptr< search::Search< PointT > > &tree, float tolerance, std::vector< PointIndices > &clusters, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)()) |
Decompose a region of space into clusters based on the Euclidean distance between points. | |
template<typename PointT > | |
void | extractEuclideanClusters (const PointCloud< PointT > &cloud, const std::vector< int > &indices, const boost::shared_ptr< search::Search< PointT > > &tree, float tolerance, std::vector< PointIndices > &clusters, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)()) |
Decompose a region of space into clusters based on the Euclidean distance between points. | |
template<typename PointT , typename Normal > | |
void | extractEuclideanClusters (const PointCloud< PointT > &cloud, const PointCloud< Normal > &normals, float tolerance, const boost::shared_ptr< KdTree< PointT > > &tree, std::vector< PointIndices > &clusters, double eps_angle, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)()) |
Decompose a region of space into clusters based on the euclidean distance between points, and the normal angular deviation. | |
template<typename PointT , typename Normal > | |
void | extractEuclideanClusters (const PointCloud< PointT > &cloud, const PointCloud< Normal > &normals, const std::vector< int > &indices, const boost::shared_ptr< KdTree< PointT > > &tree, float tolerance, std::vector< PointIndices > &clusters, double eps_angle, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)()) |
Decompose a region of space into clusters based on the euclidean distance between points, and the normal angular deviation. | |
bool | comparePointClusters (const pcl::PointIndices &a, const pcl::PointIndices &b) |
Sort clusters method (for std::sort). | |
template<typename PointT > | |
void | extractLabeledEuclideanClusters (const PointCloud< PointT > &cloud, const boost::shared_ptr< search::Search< PointT > > &tree, float tolerance, std::vector< std::vector< PointIndices > > &labeled_clusters, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)(), unsigned int max_label=(std::numeric_limits< int >::max)) |
Decompose a region of space into clusters based on the Euclidean distance between points. | |
bool | compareLabeledPointClusters (const pcl::PointIndices &a, const pcl::PointIndices &b) |
Sort clusters method (for std::sort). | |
template<typename PointT > | |
bool | isPointIn2DPolygon (const PointT &point, const pcl::PointCloud< PointT > &polygon) |
General purpose method for checking if a 3D point is inside or outside a given 2D polygon. | |
template<typename PointT > | |
bool | isXYPointIn2DXYPolygon (const PointT &point, const pcl::PointCloud< PointT > &polygon) |
Check if a 2d point (X and Y coordinates considered only!) is inside or outside a given polygon. | |
template<typename PointT > | |
void | getPointCloudDifference (const pcl::PointCloud< PointT > &src, const pcl::PointCloud< PointT > &tgt, double threshold, const boost::shared_ptr< pcl::search::Search< PointT > > &tree, pcl::PointCloud< PointT > &output) |
Obtain the difference between two aligned point clouds as another point cloud, given a distance threshold. | |
bool | 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. | |
Variables | |
struct pcl::_PointXYZHSV | EIGEN_ALIGN16 |
const int | I_SHIFT_EP [12][2] |
The 12 edges of a cell. | |
const int | I_SHIFT_PT [4] |
const int | I_SHIFT_EDGE [3][2] |
const unsigned int | edgeTable [256] |
const int | triTable [256][16] |
Software License Agreement (BSD License)
Copyright (c) 2011, Willow Garage, Inc. All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of Willow Garage, Inc. nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Author: Suat Gedikli (gedikli@willowgarage.com)
typedef Eigen::Map<Eigen::Array3f> pcl::Array3fMap |
Definition at line 151 of file point_types.hpp.
typedef const Eigen::Map<const Eigen::Array3f> pcl::Array3fMapConst |
Definition at line 152 of file point_types.hpp.
typedef Eigen::Map<Eigen::Array4f, Eigen::Aligned> pcl::Array4fMap |
Definition at line 153 of file point_types.hpp.
typedef const Eigen::Map<const Eigen::Array4f, Eigen::Aligned> pcl::Array4fMapConst |
Definition at line 154 of file point_types.hpp.
typedef BivariatePolynomialT<float> pcl::BivariatePolynomial |
Definition at line 99 of file bivariate_polynomial.h.
typedef BivariatePolynomialT<double> pcl::BivariatePolynomiald |
Definition at line 98 of file bivariate_polynomial.h.
typedef std::vector< pcl::Correspondence, Eigen::aligned_allocator<pcl::Correspondence> > pcl::Correspondences |
Definition at line 83 of file correspondence.h.
typedef boost::shared_ptr<const Correspondences > pcl::CorrespondencesConstPtr |
Definition at line 85 of file correspondence.h.
typedef boost::shared_ptr<Correspondences> pcl::CorrespondencesPtr |
Definition at line 84 of file correspondence.h.
typedef boost::shared_ptr<const std::vector<int> > pcl::IndicesConstPtr |
Definition at line 66 of file pcl_base.h.
typedef boost::shared_ptr<std::vector<int> > pcl::IndicesPtr |
Definition at line 65 of file pcl_base.h.
typedef boost::shared_ptr< ::pcl::ModelCoefficients const> pcl::ModelCoefficientsConstPtr |
Definition at line 28 of file ModelCoefficients.h.
typedef boost::shared_ptr< ::pcl::ModelCoefficients> pcl::ModelCoefficientsPtr |
Definition at line 27 of file ModelCoefficients.h.
typedef std::vector<detail::FieldMapping> pcl::MsgFieldMap |
Definition at line 64 of file point_cloud.h.
typedef std::vector<PointCorrespondence3D, Eigen::aligned_allocator<PointCorrespondence3D> > pcl::PointCorrespondences3DVector |
Definition at line 74 of file point_correspondence.h.
typedef std::vector<PointCorrespondence6D, Eigen::aligned_allocator<PointCorrespondence6D> > pcl::PointCorrespondences6DVector |
Definition at line 89 of file point_correspondence.h.
typedef boost::shared_ptr< ::pcl::PointIndices const> pcl::PointIndicesConstPtr |
Definition at line 27 of file PointIndices.h.
typedef boost::shared_ptr< ::pcl::PointIndices> pcl::PointIndicesPtr |
Definition at line 26 of file PointIndices.h.
typedef boost::shared_ptr< ::pcl::PolygonMesh const> pcl::PolygonMeshConstPtr |
Definition at line 33 of file PolygonMesh.h.
typedef boost::shared_ptr< ::pcl::PolygonMesh> pcl::PolygonMeshPtr |
Definition at line 32 of file PolygonMesh.h.
typedef PolynomialCalculationsT<float> pcl::PolynomialCalculations |
Definition at line 129 of file polynomial_calculations.h.
typedef PolynomialCalculationsT<double> pcl::PolynomialCalculationsd |
Definition at line 128 of file polynomial_calculations.h.
typedef boost::shared_ptr<pcl::TextureMesh const> pcl::TextureMeshConstPtr |
Definition at line 109 of file TextureMesh.h.
typedef boost::shared_ptr<pcl::TextureMesh> pcl::TextureMeshPtr |
Definition at line 108 of file TextureMesh.h.
typedef Eigen::Map<Eigen::Vector3f> pcl::Vector3fMap |
Definition at line 155 of file point_types.hpp.
typedef const Eigen::Map<const Eigen::Vector3f> pcl::Vector3fMapConst |
Definition at line 156 of file point_types.hpp.
typedef Eigen::Map<Eigen::Vector4f, Eigen::Aligned> pcl::Vector4fMap |
Definition at line 157 of file point_types.hpp.
typedef const Eigen::Map<const Eigen::Vector4f, Eigen::Aligned> pcl::Vector4fMapConst |
Definition at line 158 of file point_types.hpp.
typedef VectorAverage<float, 2> pcl::VectorAverage2f |
Definition at line 110 of file vector_average.h.
typedef VectorAverage<float, 3> pcl::VectorAverage3f |
Definition at line 111 of file vector_average.h.
typedef VectorAverage<float, 4> pcl::VectorAverage4f |
Definition at line 112 of file vector_average.h.
typedef boost::shared_ptr<Vertices const> pcl::VerticesConstPtr |
Definition at line 26 of file Vertices.h.
typedef boost::shared_ptr<Vertices> pcl::VerticesPtr |
Definition at line 25 of file Vertices.h.
enum pcl::SacModel |
Definition at line 45 of file model_types.h.
PCL_EXPORTS bool pcl::computePPFPairFeature | ( | const Eigen::Vector4f & | p1, |
const Eigen::Vector4f & | n1, | ||
const Eigen::Vector4f & | p2, | ||
const Eigen::Vector4f & | n2, | ||
float & | f1, | ||
float & | f2, | ||
float & | f3, | ||
float & | f4 | ||
) |
PCL_EXPORTS bool pcl::computeRGBPairFeatures | ( | const Eigen::Vector4f & | p1, |
const Eigen::Vector4f & | n1, | ||
const Eigen::Vector4i & | colors1, | ||
const Eigen::Vector4f & | p2, | ||
const Eigen::Vector4f & | n2, | ||
const Eigen::Vector4i & | colors2, | ||
float & | f1, | ||
float & | f2, | ||
float & | f3, | ||
float & | f4, | ||
float & | f5, | ||
float & | f6, | ||
float & | f7 | ||
) |
void pcl::computeRoots | ( | const Matrix & | m, |
Roots & | roots | ||
) | [inline] |
void pcl::computeRoots2 | ( | const Scalar & | b, |
const Scalar & | c, | ||
Roots & | roots | ||
) | [inline] |
pcl::PointCloud<pcl::VFHSignature308>::Ptr pcl::computeVFH | ( | typename PointCloud< PointT >::ConstPtr | cloud, |
double | radius | ||
) |
Helper function to extract the VFH feature describing the given point cloud.
points | point cloud for feature extraction |
radius | search radius for normal estimation |
Definition at line 57 of file vfh_nn_classifier.h.
void pcl::copyValueString | ( | const sensor_msgs::PointCloud2 & | cloud, |
const unsigned int | point_index, | ||
const int | point_size, | ||
const unsigned int | field_idx, | ||
const unsigned int | fields_count, | ||
std::ostream & | stream | ||
) | [inline] |
insers a value of type Type (uchar, char, uint, int, float, double, ...) into a stringstream.
If the value is NaN, it inserst "nan".
[in] | cloud | the cloud to copy from |
[in] | point_index | the index of the point |
[in] | point_size | the size of the point in the cloud |
[in] | field_idx | the index of the dimension/field |
[in] | fields_count | the current fields count |
[out] | stream | the ostringstream to copy into |
void pcl::copyValueString< int8_t > | ( | const sensor_msgs::PointCloud2 & | cloud, |
const unsigned int | point_index, | ||
const int | point_size, | ||
const unsigned int | field_idx, | ||
const unsigned int | fields_count, | ||
std::ostream & | stream | ||
) | [inline] |
void pcl::copyValueString< uint8_t > | ( | const sensor_msgs::PointCloud2 & | cloud, |
const unsigned int | point_index, | ||
const int | point_size, | ||
const unsigned int | field_idx, | ||
const unsigned int | fields_count, | ||
std::ostream & | stream | ||
) | [inline] |
void pcl::createMapping | ( | const std::vector< sensor_msgs::PointField > & | msg_fields, |
MsgFieldMap & | field_map | ||
) |
Definition at line 123 of file conversions.h.
void pcl::eigen33 | ( | const Matrix & | mat, |
Matrix & | evecs, | ||
Vector & | evals | ||
) |
void pcl::estimateRigidTransformationGICP | ( | const pcl::PointCloud< PointSource > & | cloud_src, |
const pcl::PointCloud< PointTarget > & | cloud_tgt, | ||
Eigen::Matrix4f & | transformation_matrix | ||
) | [inline] |
Estimate a rigid rotation transformation between a source and a target point cloud using the transformation estimation step from the Generalized ICP alrogithm.
Estimate a rigid rotation transformation between a source and a target point cloud using SVD.
cloud_src | the source point cloud dataset |
cloud_tgt | the target point cloud dataset |
transformation_matrix | the resultant transformation matrix |
Definition at line 43 of file stanford_gicp.hpp.
void pcl::estimateRigidTransformationGICP | ( | const pcl::PointCloud< PointSource > & | cloud_src, |
const std::vector< int > & | indices_src, | ||
const pcl::PointCloud< PointTarget > & | cloud_tgt, | ||
Eigen::Matrix4f & | transformation_matrix | ||
) | [inline] |
Estimate a rigid rotation transformation between a source and a target point cloud using the transformation estimation step from the Generalized ICP alrogithm.
Estimate a rigid rotation transformation between a source and a target point cloud using SVD.
cloud_src | the source point cloud dataset |
indices_src | the vector of indices describing the points of interest in cloud_src |
cloud_tgt | the target point cloud dataset |
transformation_matrix | the resultant transformation matrix |
Definition at line 84 of file stanford_gicp.hpp.
void pcl::estimateRigidTransformationGICP | ( | const pcl::PointCloud< PointSource > & | cloud_src, |
const std::vector< int > & | indices_src, | ||
const pcl::PointCloud< PointTarget > & | cloud_tgt, | ||
const std::vector< int > & | indices_tgt, | ||
Eigen::Matrix4f & | transformation_matrix | ||
) | [inline] |
Estimate a rigid rotation transformation between a source and a target point cloud using the transformation estimation step from the Generalized ICP alrogithm.
Estimate a rigid rotation transformation between a source and a target point cloud using SVD.
cloud_src | the source point cloud dataset |
indices_src | the vector of indices describing the points of interest in cloud_src |
cloud_tgt | the target point cloud dataset |
indices_tgt | the vector of indices describing the correspondences of the interst points from indices_src |
transformation_matrix | the resultant transformation matrix |
Definition at line 62 of file stanford_gicp.hpp.
float pcl::euclideanDistance | ( | const PointType1 & | p1, |
const PointType2 & | p2 | ||
) | [inline] |
Calculate the euclidean distance between the two given points.
Definition at line 1072 of file point_types.hpp.
void pcl::for_each_type | ( | F | f | ) | [inline] |
Definition at line 85 of file for_each_type.h.
void pcl::fromROSMsg | ( | const sensor_msgs::PointCloud2 & | msg, |
pcl::PointCloud< PointT > & | cloud, | ||
const MsgFieldMap & | field_map | ||
) |
Definition at line 154 of file conversions.h.
void pcl::fromROSMsg | ( | const sensor_msgs::PointCloud2 & | msg, |
pcl::PointCloud< PointT > & | cloud | ||
) |
Definition at line 208 of file conversions.h.
void pcl::getAllPcdFilesInDirectory | ( | const std::string & | directory, |
std::vector< std::string > & | file_names | ||
) | [inline] |
Find all *.pcd files in the directory and return them sorted.
directory | the directory to be searched |
file_names | the resulting (sorted) list of .pcd files |
Definition at line 40 of file file_io.hpp.
PCL_EXPORTS void pcl::getFieldsSizes | ( | const std::vector< sensor_msgs::PointField > & | fields, |
std::vector< int > & | field_sizes | ||
) |
Obtain a vector with the sizes of all valid fields (e.g., not "_")
[in] | fields | the input vector containing the fields |
[out] | field_sizes | the resultant field sizes in bytes |
std::string pcl::getFileExtension | ( | const std::string & | input | ) | [inline] |
Get the file extension from the given string (the remaining string after the last '.
')
input | the input filename |
Definition at line 75 of file file_io.hpp.
std::string pcl::getFilenameWithoutExtension | ( | const std::string & | input | ) | [inline] |
Remove the extension from the given string and return only the filename (everything before the last '.
')
input | the input filename (with the file extension) |
Definition at line 69 of file file_io.hpp.
std::string pcl::getFilenameWithoutPath | ( | const std::string & | input | ) | [inline] |
Remove the path from the given string and return only the filename (the remaining string after the last '/')
input | the input filename (with full path) |
Definition at line 63 of file file_io.hpp.
float pcl::getLocalRF | ( | const pcl::PointCloud< PointInT > & | cloud, |
const double | search_radius, | ||
const Eigen::Vector4f & | central_point, | ||
const std::vector< int > & | indices, | ||
const std::vector< float > & | dists, | ||
std::vector< Eigen::Vector4f, Eigen::aligned_allocator< Eigen::Vector4f > > & | rf | ||
) |
Computes disambiguated local RF for a point index.
cloud | input point cloud |
search_radius | the neighborhood radius |
central_point | the point from the input_ cloud at which the local RF is computed |
indices | the neighbours indices |
dists | the distances to the neighbours |
rf | reference frame to compute |
std::min(valid_nn_points*2/2+1, 11);
Definition at line 57 of file shot_common.hpp.
PCL_EXPORTS void pcl::getMinMax3D | ( | const sensor_msgs::PointCloud2ConstPtr & | cloud, |
int | x_idx, | ||
int | y_idx, | ||
int | z_idx, | ||
Eigen::Vector4f & | min_pt, | ||
Eigen::Vector4f & | max_pt | ||
) |
PCL_EXPORTS void pcl::getMinMax3D | ( | const sensor_msgs::PointCloud2ConstPtr & | cloud, |
int | x_idx, | ||
int | y_idx, | ||
int | z_idx, | ||
const std::string & | distance_field_name, | ||
float | min_distance, | ||
float | max_distance, | ||
Eigen::Vector4f & | min_pt, | ||
Eigen::Vector4f & | max_pt, | ||
bool | limit_negative = false |
||
) |
void pcl::getMinMax3D | ( | const typename pcl::PointCloud< PointT >::ConstPtr & | cloud, |
const std::string & | distance_field_name, | ||
float | min_distance, | ||
float | max_distance, | ||
Eigen::Vector4f & | min_pt, | ||
Eigen::Vector4f & | max_pt, | ||
bool | limit_negative = false |
||
) |
Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud, without considering points outside of a distance threshold from the laser origin.
cloud | the point cloud data message |
distance_field_name | the field name that contains the distance values |
min_distance | the minimum distance a point will be considered from |
max_distance | the maximum distance a point will be considered to |
min_pt | the resultant minimum bounds |
max_pt | the resultant maximum bounds |
limit_negative | if set to true, then all points outside of the interval (min_distance;max_distace) are considered |
Definition at line 45 of file voxel_grid.hpp.
void pcl::getRejectedQueryIndices | ( | const pcl::Correspondences & | correspondences_before, |
const pcl::Correspondences & | correspondences_after, | ||
std::vector< int > & | indices, | ||
bool | presorting_required = true |
||
) |
Get the query points of correspondences that are present in one correspondence vector but not in the other, e.g., to compare correspondences before and after rejection.
[in] | correspondences_before | Vector of correspondences before rejection |
[in] | correspondences_after | Vector of correspondences after rejection |
[out] | indices | Query point indices of correspondences that have been rejected |
[in] | presorting_required | Enable/disable internal sorting of vectors. By default (true), vectors are internally sorted before determining their difference. If the order of correspondences in correspondences_after is not different (has not been changed) from the order in correspondences_before this pre-processing step can be disabled in order to gain efficiency. In order to disable pre-sorting set presorting_requered to false. |
void pcl::getTransformationFromTwoUnitVectors | ( | const Eigen::Vector3f & | y_direction, |
const Eigen::Vector3f & | z_axis, | ||
Eigen::Affine3f & | transformation | ||
) | [inline] |
Eigen::Affine3f pcl::getTransformationFromTwoUnitVectors | ( | const Eigen::Vector3f & | y_direction, |
const Eigen::Vector3f & | z_axis | ||
) | [inline] |
bool pcl::hasValidXYZ | ( | const PointType & | p | ) | [inline] |
Checks if x,y,z are finite numbers.
Definition at line 1078 of file point_types.hpp.
PCL_EXPORTS unsigned int pcl::lzfCompress | ( | const void *const | in_data, |
unsigned int | in_len, | ||
void * | out_data, | ||
unsigned int | out_len | ||
) |
Compress in_len bytes stored at the memory block starting at in_data and write the result to out_data, up to a maximum length of out_len bytes using Marc Lehmann's LZF algorithm.
If the output buffer is not large enough or any error occurs return 0, otherwise return the number of bytes used, which might be considerably more than in_len (but less than 104% of the original size), so it makes sense to always use out_len == in_len - 1), to ensure _some_ compression, and store the data uncompressed otherwise (with a flag, of course.
[in] | in_data | the input uncompressed buffer |
[in] | in_len | the length of the input buffer |
[out] | out_data | the output buffer where the compressed result will be stored |
[out] | out_len | the length of the output buffer |
PCL_EXPORTS unsigned int pcl::lzfDecompress | ( | const void *const | in_data, |
unsigned int | in_len, | ||
void * | out_data, | ||
unsigned int | out_len | ||
) |
Decompress data compressed with the lzfCompress function and stored at location in_data and length in_len.
The result will be stored at out_data up to a maximum of out_len characters.
If the output buffer is not large enough to hold the decompressed data, a 0 is returned and errno is set to E2BIG. Otherwise the number of decompressed bytes (i.e. the original length of the data) is returned.
If an error in the compressed data is detected, a zero is returned and errno is set to EINVAL.
This function is very fast, about as fast as a copying loop.
[in] | in_data | the input compressed buffer |
[in] | in_len | the length of the input buffer |
[out] | out_data | the output buffer (must be resized to out_len) |
[out] | out_len | the length of the output buffer |
std::ostream& pcl::operator<< | ( | std::ostream & | s, |
const ::pcl::Vertices & | v | ||
) | [inline] |
Definition at line 28 of file Vertices.h.
std::ostream& pcl::operator<< | ( | std::ostream & | s, |
const ::pcl::PointIndices & | v | ||
) | [inline] |
Definition at line 29 of file PointIndices.h.
std::ostream& pcl::operator<< | ( | std::ostream & | s, |
const ::pcl::ModelCoefficients & | v | ||
) | [inline] |
Definition at line 30 of file ModelCoefficients.h.
std::ostream& pcl::operator<< | ( | std::ostream & | s, |
const ::pcl::PolygonMesh & | v | ||
) | [inline] |
Definition at line 35 of file PolygonMesh.h.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const RangeImageBorderExtractor::Parameters & | p | ||
) | [inline] |
Definition at line 57 of file range_image_border_extractor.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const Correspondence & | c | ||
) | [inline] |
overloaded << operator
Definition at line 77 of file correspondence.h.
std::ostream & pcl::operator<< | ( | std::ostream & | os, |
const BivariatePolynomialT< real > & | p | ||
) |
Definition at line 192 of file bivariate_polynomial.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointXYZ & | p | ||
) | [inline] |
Definition at line 187 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointXYZI & | p | ||
) | [inline] |
Definition at line 243 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointXYZL & | p | ||
) | [inline] |
Definition at line 262 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointXYZRGBA & | p | ||
) | [inline] |
Definition at line 315 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | s, |
const pcl::PointCloud< PointT > & | p | ||
) |
Definition at line 334 of file point_cloud.h.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointXYZRGB & | p | ||
) | [inline] |
Definition at line 413 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointXYZRGBL & | p | ||
) | [inline] |
Definition at line 434 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointXYZHSV & | p | ||
) | [inline] |
Definition at line 469 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointXY & | p | ||
) | [inline] |
Definition at line 484 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const InterestPoint & | p | ||
) | [inline] |
Definition at line 506 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const Normal & | p | ||
) | [inline] |
Definition at line 528 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointNormal & | p | ||
) | [inline] |
Definition at line 551 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointXYZRGBNormal & | p | ||
) | [inline] |
Definition at line 627 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointXYZINormal & | p | ||
) | [inline] |
Definition at line 651 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointWithRange & | p | ||
) | [inline] |
Definition at line 673 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointWithViewpoint & | p | ||
) | [inline] |
Definition at line 706 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const MomentInvariants & | p | ||
) | [inline] |
Definition at line 719 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const RangeImage & | r | ||
) | [inline] |
/ingroup range_image
Definition at line 732 of file range_image.h.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PrincipalRadiiRSD & | p | ||
) | [inline] |
Definition at line 732 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const Boundary & | p | ||
) | [inline] |
Definition at line 745 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PrincipalCurvatures & | p | ||
) | [inline] |
Definition at line 769 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PFHSignature125 & | p | ||
) | [inline] |
Definition at line 782 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PFHRGBSignature250 & | p | ||
) | [inline] |
Definition at line 796 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PPFSignature & | p | ||
) | [inline] |
Definition at line 811 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PPFRGBSignature & | p | ||
) | [inline] |
Definition at line 826 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const NormalBasedSignature12 & | p | ||
) | [inline] |
Definition at line 841 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const SHOT & | p | ||
) | [inline] |
Definition at line 857 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const FPFHSignature33 & | p | ||
) | [inline] |
Definition at line 927 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const VFHSignature308 & | p | ||
) | [inline] |
Definition at line 941 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const Narf36 & | p | ||
) | [inline] |
Definition at line 956 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const BorderDescription & | p | ||
) | [inline] |
Definition at line 974 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const IntensityGradient & | p | ||
) | [inline] |
Definition at line 996 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const Histogram< N > & | p | ||
) | [inline] |
Definition at line 1011 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointWithScale & | p | ||
) | [inline] |
Definition at line 1027 of file point_types.hpp.
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const PointSurfel & | p | ||
) | [inline] |
Definition at line 1053 of file point_types.hpp.
void pcl::PointCloudXYZRGBtoXYZHSV | ( | PointCloud< PointXYZRGB > & | in, |
PointCloud< PointXYZHSV > & | out | ||
) |
Convert a XYZRGB point cloud to a XYZHSV.
[in] | in | the input XYZRGB point cloud |
[out] | out | the output XYZHSV point cloud |
Definition at line 141 of file point_types_conversion.h.
void pcl::PointXYZHSVtoXYZRGB | ( | PointXYZHSV & | in, |
PointXYZRGB & | out | ||
) |
Convert a XYZHSV point type to a XYZRGB.
[in] | in | the input XYZHSV point |
[out] | out | the output XYZRGB point |
Definition at line 103 of file point_types_conversion.h.
void pcl::PointXYZRGBtoXYZHSV | ( | PointXYZRGB & | in, |
PointXYZHSV & | out | ||
) |
Convert a XYZRGB point type to a XYZHSV.
[in] | in | the input XYZRGB point |
[out] | out | the output XYZHSV point |
Definition at line 67 of file point_types_conversion.h.
void pcl::PointXYZRGBtoXYZI | ( | PointXYZRGB & | in, |
PointXYZI & | out | ||
) |
Convert a XYZRGB point type to a XYZI.
[in] | in | the input XYZRGB point |
[out] | out | the output XYZI point |
Definition at line 54 of file point_types_conversion.h.
void pcl::projectPoint | ( | const Point & | p, |
const Eigen::Vector4f & | model_coefficients, | ||
Point & | q | ||
) | [inline] |
Project a point on a planar model given by a set of normalized coefficients.
[in] | p | the input point to project |
[in] | model_coefficients | the coefficients of the plane (a, b, c, d) that satisfy ax+by+cz+d=0 |
[out] | q | the resultant projected point |
Definition at line 55 of file sac_model_plane.h.
float pcl::squaredEuclideanDistance | ( | const PointType1 & | p1, |
const PointType2 & | p2 | ||
) | [inline] |
Calculate the squared euclidean distance between the two given points.
Definition at line 1065 of file point_types.hpp.
void pcl::throwPCLIOException | ( | const char * | function, |
const char * | file, | ||
unsigned | line, | ||
const char * | format, | ||
... | |||
) | [inline] |
/brief /ingroup io
Definition at line 68 of file pcl_io_exception.h.
void pcl::toROSMsg | ( | const pcl::PointCloud< PointT > & | cloud, |
sensor_msgs::PointCloud2 & | msg | ||
) |
Definition at line 216 of file conversions.h.
void pcl::toROSMsg | ( | const CloudT & | cloud, |
sensor_msgs::Image & | msg | ||
) |
Copy the RGB fields of a PointCloud into sensor_msgs::Image format.
cloud | the point cloud message |
msg | the resultant sensor_msgs::Image CloudT cloud type, CloudT should be akin to pcl::PointCloud<pcl::PointXYZRGB> will throw std::runtime_error if there is a problem |
Definition at line 254 of file conversions.h.
void pcl::toROSMsg | ( | const sensor_msgs::PointCloud2 & | cloud, |
sensor_msgs::Image & | msg | ||
) | [inline] |
Copy the RGB fields of a PointCloud2 msg into sensor_msgs::Image format.
cloud | the point cloud message |
msg | the resultant sensor_msgs::Image will throw std::runtime_error if there is a problem |
Definition at line 288 of file conversions.h.
void pcl::transformPointCloudWithNormals | ( | const pcl::PointCloud< PointT > & | cloud_in, |
pcl::PointCloud< PointT > & | cloud_out, | ||
const Eigen::Affine3f & | transform | ||
) |
Transform a point cloud and rotate its normals using an Eigen transform.
cloud_in | the input point cloud |
cloud_out | the resultant output point cloud |
transform | an affine transformation (typically a rigid transformation) |
Definition at line 117 of file transforms.hpp.
const unsigned int pcl::edgeTable[256] |
Definition at line 59 of file marching_cubes.h.
const int pcl::I_SHIFT_EDGE[3][2] |
{ {0,1}, {1,3}, {1,2} }
Definition at line 58 of file grid_projection.h.
const int pcl::I_SHIFT_EP[12][2] |
{ {0, 4}, {1, 5}, {2, 6}, {3, 7}, {0, 1}, {1, 2}, {2, 3}, {3, 0}, {4, 5}, {5, 6}, {6, 7}, {7, 4} }
The 12 edges of a cell.
Definition at line 48 of file grid_projection.h.
const int pcl::I_SHIFT_PT[4] |
{ 0, 4, 5, 7 }
Definition at line 54 of file grid_projection.h.
const int pcl::triTable[256][16] |
Definition at line 93 of file marching_cubes.h.