|
struct | _Axis |
|
struct | _Intensity |
|
struct | _Intensity32u |
|
struct | _Intensity8u |
|
struct | _Normal |
|
struct | _PointDEM |
|
struct | _PointNormal |
|
struct | _PointSurfel |
|
struct | _PointWithRange |
|
struct | _PointWithScale |
|
struct | _PointWithViewpoint |
|
struct | _PointXYZ |
|
struct | _PointXYZHSV |
|
struct | _PointXYZI |
| A point structure representing Euclidean xyz coordinates, and the intensity value. More...
|
|
struct | _PointXYZINormal |
|
struct | _PointXYZL |
|
struct | _PointXYZLAB |
|
struct | _PointXYZLNormal |
|
struct | _PointXYZRGB |
|
struct | _PointXYZRGBA |
|
struct | _PointXYZRGBL |
|
struct | _PointXYZRGBNormal |
|
struct | _ReferenceFrame |
| A structure representing the Local Reference Frame of a point. More...
|
|
struct | _RGB |
|
class | AdaptiveCostSOStereoMatching |
| Adaptive Cost 2-pass Scanline Optimization Stereo Matching class. More...
|
|
class | AdaptiveRangeCoder |
| AdaptiveRangeCoder compression class More...
|
|
class | AgastKeypoint2D |
| Detects 2D AGAST corner points. More...
|
|
class | AgastKeypoint2D< pcl::PointXYZ, pcl::PointUV > |
| Detects 2D AGAST corner points. More...
|
|
class | AgastKeypoint2DBase |
| Detects 2D AGAST corner points. More...
|
|
class | ApproximateProgressiveMorphologicalFilter |
| Implements the Progressive Morphological Filter for segmentation of ground points. More...
|
|
class | ApproximateVoxelGrid |
| ApproximateVoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
|
|
class | ASCIIReader |
| Ascii Point Cloud Reader. More...
|
|
struct | Axis |
| A point structure representing an Axis using its normal coordinates. More...
|
|
class | BadArgumentException |
| An exception that is thrown when the arguments number or type is wrong/unhandled. More...
|
|
class | BearingAngleImage |
| class BearingAngleImage is used as an interface to generate Bearing Angle(BA) image. More...
|
|
class | BilateralFilter |
| A bilateral filter implementation for point cloud data. More...
|
|
class | BilateralUpsampling |
| Bilateral filtering implementation, based on the following paper: More...
|
|
class | BinaryTreeThresholdBasedBranchEstimator |
| Branch estimator for binary trees where the branch is computed only from the threshold. More...
|
|
class | BivariatePolynomialT |
| This represents a bivariate polynomial and provides some functionality for it. More...
|
|
class | BlockBasedStereoMatching |
| Block based (or fixed window) Stereo Matching class. More...
|
|
class | BOARDLocalReferenceFrameEstimation |
| BOARDLocalReferenceFrameEstimation implements the BOrder Aware Repeatable Directions algorithm for local reference frame estimation as described here: 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 | Boundary |
| A point structure representing a description of whether a point is lying on a surface boundary or not. More...
|
|
class | BoundaryEstimation |
| BoundaryEstimation estimates whether a set of points is lying on surface boundaries using an angle criterion. More...
|
|
struct | BoundingBoxXYZ |
|
class | BoxClipper3D |
| Implementation of a box clipper in 3D. Actually it allows affine transformations, thus any parallelepiped in general pose. The affine transformation is used to transform the point before clipping it using the unit cube centered at origin and with an extend of -1 to +1 in each dimension. More...
|
|
class | BranchEstimator |
| Interface for branch estimators. More...
|
|
class | BRISK2DEstimation |
| Implementation of the BRISK-descriptor, based on the original code and paper reference by. More...
|
|
class | BriskKeypoint2D |
| Detects BRISK interest points based on the original code and paper reference by. More...
|
|
struct | BRISKSignature512 |
| A point structure representing the Binary Robust Invariant Scalable Keypoints (BRISK). More...
|
|
class | CentroidPoint |
| A generic class that computes the centroid of points fed to it. More...
|
|
class | Clipper3D |
| Base class for 3D clipper objects. More...
|
|
class | CloudIterator |
| Iterator class for point clouds with or without given indices. More...
|
|
class | CloudSurfaceProcessing |
| CloudSurfaceProcessing represents the base class for algorithms that takes a point cloud as input and produces a new output cloud that has been modified towards a better surface representation. More...
|
|
class | ColorGradientDOTModality |
|
class | ColorGradientModality |
| Modality based on max-RGB gradients. More...
|
|
class | ColorLUT |
|
class | ColorModality |
|
class | Comparator |
| Comparator is the base class for comparators that compare two points given some function. More...
|
|
class | ComparisonBase |
| The (abstract) base class for the comparison object. More...
|
|
class | ComputeFailedException |
|
class | ConcaveHull |
| ConcaveHull (alpha shapes) using libqhull library. More...
|
|
class | ConditionalEuclideanClustering |
| ConditionalEuclideanClustering performs segmentation based on Euclidean distance and a user-defined clustering condition. More...
|
|
class | ConditionalRemoval |
| ConditionalRemoval filters data that satisfies certain conditions. More...
|
|
class | ConditionAnd |
| AND condition. More...
|
|
class | ConditionBase |
| Base condition class. More...
|
|
class | ConditionOr |
| OR condition. More...
|
|
class | ConstCloudIterator |
| Iterator class for point clouds with or without given indices. More...
|
|
class | ConvexHull |
| ConvexHull using libqhull library. More...
|
|
class | Convolution |
| A 2D convolution class. More...
|
|
struct | CopyIfFieldExists |
| A helper functor that can copy a specific value if the given field exists. More...
|
|
struct | Correspondence |
| Correspondence represents a match between two entities (e.g., points, descriptors, etc). More...
|
|
class | CorrespondenceGrouping |
| Abstract base class for Correspondence Grouping algorithms. More...
|
|
class | CovarianceSampling |
| Point Cloud sampling based on the 6D covariances. More...
|
|
class | CPCSegmentation |
| A segmentation algorithm partitioning a supervoxel graph. More...
|
|
class | CPPFEstimation |
| Class that calculates the "surflet" features for each pair in the given pointcloud. More...
|
|
struct | CPPFSignature |
| A point structure for storing the Point Pair Feature (CPPF) values. More...
|
|
class | CrfNormalSegmentation |
|
class | CrfSegmentation |
|
class | CRHAlignment |
| CRHAlignment uses two Camera Roll Histograms (CRH) to find the roll rotation that aligns both views. More...
|
|
class | CRHEstimation |
| CRHEstimation estimates the Camera Roll Histogram (CRH) descriptor for a given point cloud dataset containing XYZ data and normals, as presented in: More...
|
|
class | CropBox |
| CropBox is a filter that allows the user to filter all the data inside of a given box. More...
|
|
class | CropBox< pcl::PCLPointCloud2 > |
| CropBox is a filter that allows the user to filter all the data inside of a given box. More...
|
|
class | CropHull |
| Filter points that lie inside or outside a 3D closed surface or 2D closed polygon, as generated by the ConvexHull or ConcaveHull classes. More...
|
|
class | CustomPointRepresentation |
| CustomPointRepresentation extends PointRepresentation to allow for sub-part selection on the point. More...
|
|
class | CVFHEstimation |
| CVFHEstimation estimates the Clustered Viewpoint Feature Histogram (CVFH) descriptor for a given point cloud dataset containing XYZ data and normals, as presented in: More...
|
|
class | DavidSDKGrabber |
| Grabber for davidSDK structured light compliant devices. More...
|
|
class | DecisionForest |
| Class representing a decision forest. More...
|
|
class | DecisionForestEvaluator |
| Utility class for evaluating a decision forests. More...
|
|
class | DecisionForestTrainer |
| Trainer for decision trees. More...
|
|
class | DecisionTree |
| Class representing a decision tree. More...
|
|
class | DecisionTreeEvaluator |
| Utility class for evaluating a decision tree. More...
|
|
class | DecisionTreeTrainer |
| Trainer for decision trees. More...
|
|
class | DecisionTreeTrainerDataProvider |
|
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 | DefaultIterator |
|
class | DefaultPointRepresentation |
| DefaultPointRepresentation extends PointRepresentation to define default behavior for common point types. More...
|
|
class | DefaultPointRepresentation< FPFHSignature33 > |
|
class | DefaultPointRepresentation< GASDSignature512 > |
|
class | DefaultPointRepresentation< GASDSignature7992 > |
|
class | DefaultPointRepresentation< GASDSignature984 > |
|
class | DefaultPointRepresentation< Narf36 > |
|
class | DefaultPointRepresentation< NormalBasedSignature12 > |
|
class | DefaultPointRepresentation< PFHRGBSignature250 > |
|
class | DefaultPointRepresentation< PFHSignature125 > |
|
class | DefaultPointRepresentation< PointNormal > |
|
class | DefaultPointRepresentation< PointXYZ > |
|
class | DefaultPointRepresentation< PointXYZI > |
|
class | DefaultPointRepresentation< PPFSignature > |
|
class | DefaultPointRepresentation< ShapeContext1980 > |
|
class | DefaultPointRepresentation< SHOT1344 > |
|
class | DefaultPointRepresentation< SHOT352 > |
|
class | DefaultPointRepresentation< UniqueShapeContext1960 > |
|
class | DefaultPointRepresentation< VFHSignature308 > |
|
class | DenseCrf |
|
struct | DenseQuantizedMultiModTemplate |
|
struct | DenseQuantizedSingleModTemplate |
|
class | DepthSenseGrabber |
| Grabber for DepthSense devices (e.g. More...
|
|
class | DifferenceOfNormalsEstimation |
| A Difference of Normals (DoN) scale filter implementation for point cloud data. More...
|
|
class | DigitalElevationMapBuilder |
| Build a Digital Elevation Map in the column-disparity space from a disparity map and a color image of the scene. More...
|
|
class | DinastGrabber |
| Grabber for DINAST devices (i.e., IPA-1002, IPA-1110, IPA-2001) More...
|
|
class | DisparityMapConverter |
| Compute point cloud from the disparity map. More...
|
|
class | DistanceMap |
| Represents a distance map obtained from a distance transformation. More...
|
|
class | DOTMOD |
| Template matching using the DOTMOD approach. More...
|
|
class | DOTModality |
|
struct | DOTMODDetection |
|
class | EarClipping |
| The ear clipping triangulation algorithm. More...
|
|
class | Edge |
|
class | EdgeAwarePlaneComparator |
| EdgeAwarePlaneComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
|
|
class | EnergyMaps |
| Stores a set of energy maps. More...
|
|
class | EnsensoGrabber |
| Grabber for IDS-Imaging Ensenso's devices. More...
|
|
class | ESFEstimation |
| ESFEstimation estimates the ensemble of shape functions descriptors for a given point cloud dataset containing points. More...
|
|
struct | ESFSignature640 |
| A point structure representing the Ensemble of Shape Functions (ESF). More...
|
|
class | EuclideanClusterComparator |
| EuclideanClusterComparator is a comparator used for finding clusters based on euclidian distance. More...
|
|
class | EuclideanClusterExtraction |
| EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense. More...
|
|
class | EuclideanPlaneCoefficientComparator |
| EuclideanPlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
|
|
class | EventFrequency |
| A helper class to measure frequency of a certain event. More...
|
|
class | ExtractIndices |
| ExtractIndices extracts a set of indices from a point cloud. More...
|
|
class | ExtractIndices< pcl::PCLPointCloud2 > |
| ExtractIndices extracts a set of indices from a point cloud. 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 | FastBilateralFilter |
| Implementation of a fast bilateral filter for smoothing depth information in organized point clouds Based on the following paper: More...
|
|
class | FastBilateralFilterOMP |
| Implementation of a fast bilateral filter for smoothing depth information in organized point clouds Based on the following paper: More...
|
|
class | Feature |
| Feature represents the base feature class. More...
|
|
class | FeatureFromLabels |
|
class | FeatureFromNormals |
|
class | FeatureHandler |
| Utility class interface which is used for creating and evaluating features. More...
|
|
class | FeatureHistogram |
| Type for histograms for computing mean and variance of some floats. More...
|
|
class | FeatureWithLocalReferenceFrames |
| FeatureWithLocalReferenceFrames provides a public interface for descriptor extractor classes which need a local reference frame at each input keypoint. More...
|
|
class | Fern |
| Class representing a Fern. More...
|
|
class | FernEvaluator |
| Utility class for evaluating a fern. More...
|
|
class | FernTrainer |
| Trainer for a Fern. More...
|
|
class | FieldComparison |
| The field-based specialization of the comparison object. More...
|
|
struct | FieldMatches |
|
class | FileGrabber |
| FileGrabber provides a container-style interface for grabbers which operate on fixed-size input. More...
|
|
class | FileReader |
| Point Cloud Data (FILE) file format reader interface. More...
|
|
class | FileWriter |
| Point Cloud Data (FILE) file format writer. More...
|
|
class | Filter |
| Filter represents the base filter class. More...
|
|
class | Filter< pcl::PCLPointCloud2 > |
| Filter represents the base filter class. More...
|
|
class | FilterIndices |
| FilterIndices represents the base class for filters that are about binary point removal. More...
|
|
class | FilterIndices< pcl::PCLPointCloud2 > |
| FilterIndices represents the base class for filters that are about binary point removal. More...
|
|
class | FLARELocalReferenceFrameEstimation |
| FLARELocalReferenceFrameEstimation implements the Fast LocAl Reference framE algorithm for local reference frame estimation as described here: More...
|
|
struct | for_each_type_impl |
|
struct | for_each_type_impl< false > |
|
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 | FPFHSignature33 |
| A point structure representing the Fast Point Feature Histogram (FPFH). More...
|
|
class | FrustumCulling |
| FrustumCulling filters points inside a frustum given by pose and field of view of the camera. 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) depending on the chosen _Scalar. More...
|
|
class | GASDColorEstimation |
| GASDColorEstimation estimates the Globally Aligned Spatial Distribution (GASD) descriptor for a given point cloud dataset given XYZ and RGB data. More...
|
|
class | GASDEstimation |
| GASDEstimation estimates the Globally Aligned Spatial Distribution (GASD) descriptor for a given point cloud dataset given XYZ data. More...
|
|
struct | GASDSignature512 |
| A point structure representing the Globally Aligned Spatial Distribution (GASD) shape descriptor. More...
|
|
struct | GASDSignature7992 |
| A point structure representing the Globally Aligned Spatial Distribution (GASD) shape and color descriptor. More...
|
|
struct | GASDSignature984 |
| A point structure representing the Globally Aligned Spatial Distribution (GASD) shape and color descriptor. More...
|
|
class | GaussianKernel |
| Class GaussianKernel assembles all the method for computing, convolving, smoothing, gradients computing an image using a gaussian kernel. 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 | GeometricConsistencyGrouping |
| Class implementing a 3D correspondence grouping enforcing geometric consistency among feature correspondences. More...
|
|
class | GFPFHEstimation |
| GFPFHEstimation estimates the Global Fast Point Feature Histogram (GFPFH) descriptor for a given point cloud dataset containing points and labels. More...
|
|
struct | GFPFHSignature16 |
| A point structure representing the GFPFH descriptor with 16 bins. More...
|
|
class | GlobalHypothesesVerification |
| A hypothesis verification method proposed in "A Global Hypotheses Verification Method for 3D Object Recognition", A. More...
|
|
class | Grabber |
| Grabber interface for PCL 1.x device drivers. More...
|
|
class | GrabCut |
| Implementation of the GrabCut segmentation in "GrabCut — Interactive Foreground Extraction using Iterated Graph Cuts" by Carsten Rother, Vladimir Kolmogorov and Andrew Blake. More...
|
|
struct | GradientXY |
| A point structure representing Euclidean xyz coordinates, and the intensity value. More...
|
|
class | GraphRegistration |
| GraphRegistration class is the base class for graph-based registration methods More...
|
|
class | GrayStereoMatching |
| Stereo Matching abstract class for Grayscale images. More...
|
|
class | GreedyProjectionTriangulation |
| GreedyProjectionTriangulation is an implementation of a greedy triangulation algorithm for 3D points based on local 2D projections. More...
|
|
class | GreedyVerification |
| A greedy hypothesis verification method. More...
|
|
class | GridMinimum |
| GridMinimum assembles a local 2D grid over a given PointCloud, and downsamples the data. More...
|
|
class | GridProjection |
| Grid projection surface reconstruction method. More...
|
|
class | GroundPlaneComparator |
| GroundPlaneComparator is a Comparator for detecting smooth surfaces suitable for driving. More...
|
|
class | GRSDEstimation |
| GRSDEstimation estimates the Global Radius-based Surface Descriptor (GRSD) for a given point cloud dataset containing points and normals. More...
|
|
struct | GRSDSignature21 |
| A point structure representing the Global Radius-based Surface Descriptor (GRSD). More...
|
|
class | HarrisKeypoint2D |
| HarrisKeypoint2D detects Harris corners family points. More...
|
|
class | HarrisKeypoint3D |
| HarrisKeypoint3D uses the idea of 2D Harris keypoints, but instead of using image gradients, it uses surface normals. More...
|
|
class | HarrisKeypoint6D |
| Keypoint detector for detecting corners in 3D (XYZ), 2D (intensity) AND mixed versions of these. More...
|
|
struct | has_custom_allocator |
| Tests at compile time if type T has a custom allocator. More...
|
|
class | HashTableOLD |
|
class | HDLGrabber |
| Grabber for the Velodyne High-Definition-Laser (HDL) More...
|
|
struct | Histogram |
| A point structure representing an N-D histogram. More...
|
|
class | Hough3DGrouping |
| Class implementing a 3D correspondence grouping algorithm that can deal with multiple instances of a model template found into a given scene. More...
|
|
class | HypothesisVerification |
| Abstract class for hypotheses verification methods. More...
|
|
class | IFSReader |
| Indexed Face set (IFS) file format reader. More...
|
|
class | IFSWriter |
| Point Cloud Data (IFS) file format writer. More...
|
|
class | ImageGrabber |
|
class | ImageGrabberBase |
| Base class for Image file grabber. More...
|
|
class | InitFailedException |
| An exception thrown when init can not be performed should be used in all the PCLBase class inheritants. More...
|
|
class | IntegralImage2D |
| Determines an integral image representation for a given organized data array. More...
|
|
class | IntegralImage2D< DataType, 1 > |
| partial template specialization for integral images with just one channel. More...
|
|
class | IntegralImageNormalEstimation |
| Surface normal estimation on organized data using integral images. More...
|
|
struct | IntegralImageTypeTraits |
|
struct | IntegralImageTypeTraits< char > |
|
struct | IntegralImageTypeTraits< float > |
|
struct | IntegralImageTypeTraits< int > |
|
struct | IntegralImageTypeTraits< short > |
|
struct | IntegralImageTypeTraits< unsigned char > |
|
struct | IntegralImageTypeTraits< unsigned int > |
|
struct | IntegralImageTypeTraits< unsigned short > |
|
struct | Intensity |
| A point structure representing the grayscale intensity in single-channel images. More...
|
|
struct | Intensity32u |
| A point structure representing the grayscale intensity in single-channel images. More...
|
|
struct | Intensity8u |
| A point structure representing the grayscale intensity in single-channel images. More...
|
|
struct | IntensityGradient |
| A point structure representing the intensity gradient of an XYZI point cloud. 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...
|
|
struct | InterestPoint |
| A point structure representing an interest point with Euclidean xyz coordinates, and an interest value. More...
|
|
struct | intersect |
|
class | InvalidConversionException |
| An exception that is thrown when a PCLPointCloud2 message cannot be converted into a PCL type. 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 | ISMPeak |
| This struct is used for storing peak. More...
|
|
class | IsNotDenseException |
| An exception that is thrown when a PointCloud is not dense but is attempted to be used as dense. More...
|
|
class | ISSKeypoint3D |
| ISSKeypoint3D detects the Intrinsic Shape Signatures keypoints for a given point cloud. 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 | IterativeClosestPointWithNormals |
| IterativeClosestPointWithNormals is a special case of IterativeClosestPoint, that uses a transformation estimated based on Point to Plane distances by default. More...
|
|
class | IteratorIdx |
|
class | JointIterativeClosestPoint |
| JointIterativeClosestPoint extends ICP to multiple frames which share the same transform. More...
|
|
class | KdTree |
| KdTree represents the base spatial locator class for kd-tree implementations. More...
|
|
class | KdTreeFLANN |
| KdTreeFLANN is a generic type of 3D spatial locator using kD-tree structures. More...
|
|
class | kernel |
|
class | KernelWidthTooSmallException |
| An exception that is thrown when the kernel size is too small. More...
|
|
class | Keypoint |
| Keypoint represents the base class for key points. More...
|
|
class | Kmeans |
| K-means clustering. More...
|
|
struct | Label |
|
class | LabeledEuclideanClusterExtraction |
| LabeledEuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense, with label info. More...
|
|
class | LCCPSegmentation |
| A simple segmentation algorithm partitioning a supervoxel graph into groups of locally convex connected supervoxels separated by concave borders. More...
|
|
class | LeastMedianSquares |
| LeastMedianSquares represents an implementation of the LMedS (Least Median of Squares) algorithm. More...
|
|
class | LinearizedMaps |
| Stores a set of linearized maps. More...
|
|
class | LinearLeastSquaresNormalEstimation |
| Surface normal estimation on dense data using a least-squares estimation based on a first-order Taylor approximation. More...
|
|
class | LineIterator |
| Organized Index Iterator for iterating over the "pixels" for a given line using the Bresenham algorithm. More...
|
|
class | LINEMOD |
| Template matching using the LINEMOD approach. More...
|
|
struct | LINEMOD_OrientationMap |
| Map that stores orientations. More...
|
|
struct | LINEMODDetection |
| Represents a detection of a template using the LINEMOD approach. More...
|
|
class | LineRGBD |
| High-level class for template matching using the LINEMOD approach based on RGB and Depth data. More...
|
|
class | LocalMaximum |
| LocalMaximum downsamples the cloud, by eliminating points that are locally maximal. More...
|
|
class | MarchingCubes |
| The marching cubes surface reconstruction algorithm. More...
|
|
class | MarchingCubesHoppe |
| The marching cubes surface reconstruction algorithm, using a signed distance function based on the distance from tangent planes, proposed by Hoppe et. More...
|
|
class | MarchingCubesRBF |
| The marching cubes surface reconstruction algorithm, using a signed distance function based on radial basis functions. More...
|
|
class | MaskMap |
|
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 | MedianFilter |
| Implementation of the median filter. More...
|
|
class | MeshConstruction |
| MeshConstruction represents a base surface reconstruction class. More...
|
|
class | MeshProcessing |
| MeshProcessing represents the base class for mesh processing algorithms. More...
|
|
class | MeshQuadricDecimationVTK |
| PCL mesh decimation based on vtkQuadricDecimation from the VTK library. More...
|
|
class | MeshSmoothingLaplacianVTK |
| PCL mesh smoothing based on the vtkSmoothPolyDataFilter algorithm from the VTK library. More...
|
|
class | MeshSmoothingWindowedSincVTK |
| PCL mesh smoothing based on the vtkWindowedSincPolyDataFilter algorithm from the VTK library. More...
|
|
class | MeshSubdivisionVTK |
| PCL mesh smoothing based on the vtkLinearSubdivisionFilter, vtkLoopSubdivisionFilter, vtkButterflySubdivisionFilter depending on the selected MeshSubdivisionVTKFilterType algorithm from the VTK library. 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 | MinCutSegmentation |
| This class implements the segmentation algorithm based on minimal cut of the graph. More...
|
|
struct | MLSResult |
| Data structure used to store the results of the MLS fitting. More...
|
|
struct | ModelCoefficients |
|
class | ModelOutlierRemoval |
| ModelOutlierRemoval filters points in a cloud based on the distance between model and point. More...
|
|
struct | MomentInvariants |
| A point structure representing the three moment invariants. More...
|
|
class | MomentInvariantsEstimation |
| MomentInvariantsEstimation estimates the 3 moment invariants (j1, j2, j3) at each 3D point. More...
|
|
class | MomentOfInertiaEstimation |
| Implements the method for extracting features based on moment of inertia. More...
|
|
class | Morphology |
|
class | MovingLeastSquares |
| MovingLeastSquares represent an implementation of the MLS (Moving Least Squares) algorithm for data smoothing and improved normal estimation. More...
|
|
class | MTLReader |
|
class | MultiChannel2DComparisonFeature |
| Feature for comparing two sample points in 2D multi-channel data. More...
|
|
class | MultiChannel2DComparisonFeatureHandler |
| Feature utility class that handles the creation and evaluation of RGBD comparison features. More...
|
|
class | MultiChannel2DData |
| Holds two-dimensional multi-channel data. More...
|
|
class | MultiChannel2DDataSet |
| Holds a set of two-dimensional multi-channel data. More...
|
|
struct | MultipleData2DExampleIndex |
| Example index for a set of 2D data blocks. 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...
|
|
struct | Narf36 |
| A point structure representing the Narf descriptor. More...
|
|
class | NarfDescriptor |
| Computes NARF feature descriptors for points in a range image See B. More...
|
|
class | NarfKeypoint |
| NARF (Normal Aligned Radial Feature) keypoints. More...
|
|
struct | NdCentroidFunctor |
| Helper functor structure for n-D centroid estimation. More...
|
|
struct | NdConcatenateFunctor |
| Helper functor structure for concatenate. More...
|
|
struct | NdCopyEigenPointFunctor |
| Helper functor structure for copying data between an Eigen type and a PointT. More...
|
|
struct | NdCopyPointEigenFunctor |
| Helper functor structure for copying data between an Eigen type and a PointT. More...
|
|
struct | Normal |
| A point structure representing normal coordinates and the surface curvature estimate. More...
|
|
struct | NormalBasedSignature12 |
| A point structure representing the Normal Based Signature for a feature matrix of 4-by-3. More...
|
|
class | NormalBasedSignatureEstimation |
| Normal-based feature signature estimation class. More...
|
|
class | NormalDistributionsTransform |
| A 3D Normal Distribution Transform registration implementation for point cloud data. More...
|
|
class | NormalDistributionsTransform2D |
| NormalDistributionsTransform2D provides an implementation of the Normal Distributions Transform algorithm for scan matching. More...
|
|
class | NormalEstimation |
| NormalEstimation estimates local surface properties (surface normals and curvatures)at each 3D point. 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 | NormalRefinement |
| Normal vector refinement class More...
|
|
class | NormalSpaceSampling |
| NormalSpaceSampling samples the input point cloud in the space of normal directions computed at every point. More...
|
|
class | NotEnoughPointsException |
| An exception that is thrown when the number of correspondents is not equal to the minimum required. More...
|
|
class | OBJReader |
|
class | ONIGrabber |
| A simple ONI grabber. More...
|
|
class | OpenNIGrabber |
| Grabber for OpenNI devices (i.e., Primesense PSDK, Microsoft Kinect, Asus XTion Pro/Live) More...
|
|
class | OrganizedConnectedComponentSegmentation |
| OrganizedConnectedComponentSegmentation allows connected components to be found within organized point cloud data, given a comparison function. More...
|
|
class | OrganizedEdgeBase |
| OrganizedEdgeBase, OrganizedEdgeFromRGB, OrganizedEdgeFromNormals, and OrganizedEdgeFromRGBNormals find 3D edges from an organized point cloud data. More...
|
|
class | OrganizedEdgeFromNormals |
|
class | OrganizedEdgeFromRGB |
|
class | OrganizedEdgeFromRGBNormals |
|
class | OrganizedFastMesh |
| Simple triangulation/surface reconstruction for organized point clouds. More...
|
|
class | OrganizedIndexIterator |
| base class for iterators on 2-dimensional maps like images/organized clouds etc. More...
|
|
class | OrganizedMultiPlaneSegmentation |
| OrganizedMultiPlaneSegmentation finds all planes present in the input cloud, and outputs a vector of plane equations, as well as a vector of point clouds corresponding to the inliers of each detected plane. More...
|
|
class | OrganizedNeighborSearch |
| OrganizedNeighborSearch class More...
|
|
class | OURCVFHEstimation |
| OURCVFHEstimation estimates the Oriented, Unique and Repetable Clustered Viewpoint Feature Histogram (CVFH) descriptor for a given point cloud dataset given XYZ data and normals, as presented in: More...
|
|
class | PackedHSIComparison |
| A packed HSI specialization of the comparison object. More...
|
|
class | PackedRGBComparison |
| A packed rgb specialization of the comparison object. More...
|
|
class | PairwiseGraphRegistration |
| PairwiseGraphRegistration class aligns the clouds two by two More...
|
|
class | PairwisePotential |
|
class | PapazovHV |
| A hypothesis verification method proposed in "An Efficient RANSAC for 3D Object Recognition in Noisy and Occluded Scenes", C. More...
|
|
class | PassThrough |
| PassThrough passes points in a cloud based on constraints for one particular field of the point type. More...
|
|
class | PassThrough< pcl::PCLPointCloud2 > |
| PassThrough uses the base Filter class methods to pass through all data that satisfies the user given constraints. More...
|
|
class | PCA |
| Principal Component analysis (PCA) class. More...
|
|
class | PCDGrabber |
|
class | PCDGrabberBase |
| Base class for PCD file grabber. More...
|
|
class | PCDReader |
| Point Cloud Data (PCD) file format reader. More...
|
|
class | PCDWriter |
| Point Cloud Data (PCD) file format writer. More...
|
|
class | PCLBase |
| PCL base class. More...
|
|
class | PCLBase< pcl::PCLPointCloud2 > |
|
class | PCLException |
| A base class for all pcl exceptions which inherits from std::runtime_error. More...
|
|
struct | PCLHeader |
|
struct | PCLImage |
|
struct | PCLPointCloud2 |
|
struct | PCLPointField |
|
class | PCLSurfaceBase |
| Pure abstract class. More...
|
|
class | Permutohedral |
| Implementation of a high-dimensional gaussian filtering using the permutohedral lattice. More...
|
|
class | PFHEstimation |
| PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals. More...
|
|
class | PFHRGBEstimation |
|
struct | PFHRGBSignature250 |
| A point structure representing the Point Feature Histogram with colors (PFHRGB). More...
|
|
struct | PFHSignature125 |
| A point structure representing the Point Feature Histogram (PFH). More...
|
|
class | PiecewiseLinearFunction |
| This provides functionalities to efficiently return values for piecewise linear function. More...
|
|
class | PlanarPolygon |
| PlanarPolygon represents a planar (2D) polygon, potentially in a 3D space. More...
|
|
class | PlanarPolygonFusion |
| PlanarPolygonFusion takes a list of 2D planar polygons and attempts to reduce them to a minimum set that best represents the scene, based on various given comparators. More...
|
|
class | PlanarRegion |
| PlanarRegion represents a set of points that lie in a plane. More...
|
|
class | PlaneClipper3D |
| Implementation of a plane clipper in 3D. More...
|
|
class | PlaneCoefficientComparator |
| PlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
|
|
class | PlaneRefinementComparator |
| PlaneRefinementComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
|
|
class | PLYReader |
| Point Cloud Data (PLY) file format reader. More...
|
|
class | PLYWriter |
| Point Cloud Data (PLY) file format writer. More...
|
|
class | PointCloud |
| PointCloud represents the base class in PCL for storing collections of 3D points. 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 | PointDataAtOffset |
| A datatype that enables type-correct comparisons. More...
|
|
struct | PointDEM |
| A point structure representing Digital Elevation Map. More...
|
|
struct | PointIndices |
|
struct | PointNormal |
| A point structure representing Euclidean xyz coordinates, together with normal coordinates and the surface curvature estimate. More...
|
|
class | PointRepresentation |
| PointRepresentation provides a set of methods for converting a point structs/object into an n-dimensional vector. 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 | PointUV |
| A 2D point structure representing pixel image coordinates. More...
|
|
struct | PointWithRange |
| A point structure representing Euclidean xyz coordinates, padded with an extra range float. More...
|
|
struct | PointWithScale |
| A point structure representing a 3-D position and scale. More...
|
|
struct | PointWithViewpoint |
| A point structure representing Euclidean xyz coordinates together with the viewpoint from which it was seen. More...
|
|
struct | PointXY |
| A 2D point structure representing Euclidean xy coordinates. More...
|
|
class | PointXY32f |
| 2D point with float x- and y-coordinates. More...
|
|
class | PointXY32i |
| 2D point with integer x- and y-coordinates. More...
|
|
struct | PointXYZ |
| A point structure representing Euclidean xyz coordinates. More...
|
|
struct | PointXYZHSV |
|
struct | PointXYZI |
|
struct | PointXYZIEdge |
| Point cloud containing edge information. More...
|
|
struct | PointXYZINormal |
| A point structure representing Euclidean xyz coordinates, intensity, together with normal coordinates and the surface curvature estimate. More...
|
|
struct | PointXYZL |
|
struct | PointXYZLAB |
| A custom point type for position and CIELAB color value. More...
|
|
struct | PointXYZLNormal |
| A point structure representing Euclidean xyz coordinates, a label, together with normal coordinates and the surface curvature estimate. More...
|
|
struct | PointXYZRGB |
| A point structure representing Euclidean xyz coordinates, and the RGB color. More...
|
|
struct | PointXYZRGBA |
| A point structure representing Euclidean xyz coordinates, and the RGBA color. More...
|
|
struct | PointXYZRGBL |
|
struct | PointXYZRGBNormal |
| A point structure representing Euclidean xyz coordinates, and the RGB color, together with normal coordinates and the surface curvature estimate. More...
|
|
class | Poisson |
| The Poisson surface reconstruction algorithm. More...
|
|
struct | PolygonMesh |
|
class | PolynomialCalculationsT |
| This provides some functionality for polynomials, like finding roots or approximating bivariate polynomials. More...
|
|
class | PosesFromMatches |
| calculate 3D transformation based on point correspondences More...
|
|
class | PPFEstimation |
| Class that calculates the "surflet" features for each pair in the given pointcloud. More...
|
|
class | PPFHashMapSearch |
|
class | PPFRegistration |
| Class that registers two point clouds based on their sets of PPFSignatures. More...
|
|
class | PPFRGBEstimation |
|
class | PPFRGBRegionEstimation |
|
struct | PPFRGBSignature |
| A point structure for storing the Point Pair Color Feature (PPFRGB) values. More...
|
|
struct | PPFSignature |
| A point structure for storing the Point Pair Feature (PPF) values. More...
|
|
struct | PrincipalCurvatures |
| A point structure representing the principal curvatures and their magnitudes. More...
|
|
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...
|
|
struct | PrincipalRadiiRSD |
| A point structure representing the minimum and maximum surface radii (in meters) computed using RSD. More...
|
|
class | ProgressiveMorphologicalFilter |
| Implements the Progressive Morphological Filter for segmentation of ground points. More...
|
|
class | ProgressiveSampleConsensus |
| ProgressiveSampleConsensus represents an implementation of the PROSAC (PROgressive SAmple Consensus) algorithm, as described in: "Matching with PROSAC – Progressive Sample Consensus", Chum, O. 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< pcl::PCLPointCloud2 > |
| ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud. More...
|
|
class | PyramidFeatureHistogram |
| Class that compares two sets of features by using a multiscale representation of the features inside a pyramid. More...
|
|
class | QuantizableModality |
| Interface for a quantizable modality. More...
|
|
class | QuantizedMap |
|
struct | QuantizedMultiModFeature |
| Feature that defines a position and quantized value in a specific modality. More...
|
|
struct | QuantizedNormalLookUpTable |
| Look-up-table for fast surface normal quantization. More...
|
|
class | RadiusOutlierRemoval |
| RadiusOutlierRemoval filters points in a cloud based on the number of neighbors they have. More...
|
|
class | RadiusOutlierRemoval< pcl::PCLPointCloud2 > |
| 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 | 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 | RandomSample |
| RandomSample applies a random sampling with uniform probability. More...
|
|
class | RandomSample< pcl::PCLPointCloud2 > |
| RandomSample applies a random sampling with uniform probability. 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 | 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 | RangeImageBorderExtractor |
| Extract obstacle borders from range images, meaning positions where there is a transition from foreground to background. 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 | RangeImageSpherical |
| RangeImageSpherical is derived from the original range image and uses a slightly different spherical projection. More...
|
|
class | RealSense2Grabber |
| Grabber for Intel Realsense 2 SDK devices (D400 series) More...
|
|
class | RealSenseGrabber |
|
struct | ReferenceFrame |
|
class | Region3D |
| Region3D represents summary statistics of a 3D collection of points. More...
|
|
class | RegionGrowing |
| Implements the well known Region Growing algorithm used for segmentation. More...
|
|
class | RegionGrowingRGB |
| Implements the well known Region Growing algorithm used for segmentation based on color of points. More...
|
|
struct | RegionXY |
| Defines a region in XY-space. More...
|
|
class | Registration |
| Registration represents the base registration class for general purpose, ICP-like methods. More...
|
|
class | RegistrationVisualizer |
| RegistrationVisualizer represents the base class for rendering the intermediate positions occupied by the source point cloud during it's registration to the target point cloud. More...
|
|
class | RegressionVarianceNode |
| Node for a regression trees which optimizes variance. More...
|
|
class | RegressionVarianceStatsEstimator |
| Statistics estimator for regression trees which optimizes variance. More...
|
|
class | RFFaceDetectorTrainer |
|
struct | RGB |
| A structure representing RGB color information. More...
|
|
class | RGBPlaneCoefficientComparator |
| RGBPlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
|
|
class | RIFTEstimation |
| RIFTEstimation estimates the Rotation Invariant Feature Transform descriptors for a given point cloud dataset containing points and intensity. More...
|
|
class | RobotEyeGrabber |
| Grabber for the Ocular Robotics RobotEye sensor. More...
|
|
class | ROPSEstimation |
| This class implements the method for extracting RoPS features presented in the article "Rotational Projection Statistics for 3D Local Surface Description and Object Recognition" by Yulan Guo, Ferdous Sohel, Mohammed Bennamoun, Min Lu and Jianwei Wan. 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 | 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 | SampleConsensus |
| SampleConsensus represents the base class. 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 | SampleConsensusModel |
| SampleConsensusModel represents the base model class. More...
|
|
class | SampleConsensusModelCircle2D |
| SampleConsensusModelCircle2D defines a model for 2D circle segmentation on the X-Y plane. More...
|
|
class | SampleConsensusModelCircle3D |
| SampleConsensusModelCircle3D defines a model for 3D circle segmentation. More...
|
|
class | SampleConsensusModelCone |
| SampleConsensusModelCone defines a model for 3D cone segmentation. More...
|
|
class | SampleConsensusModelCylinder |
| SampleConsensusModelCylinder defines a model for 3D cylinder segmentation. More...
|
|
class | SampleConsensusModelFromNormals |
| SampleConsensusModelFromNormals represents the base model class for models that require the use of surface normals for estimation. 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 | SampleConsensusModelNormalSphere |
| SampleConsensusModelNormalSphere defines a model for 3D sphere 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 | SampleConsensusModelRegistration2D |
| SampleConsensusModelRegistration2D defines a model for Point-To-Point registration outlier rejection using distances between 2D pixels. More...
|
|
class | SampleConsensusModelSphere |
| SampleConsensusModelSphere defines a model for 3D sphere segmentation. More...
|
|
class | SampleConsensusModelStick |
| SampleConsensusModelStick defines a model for 3D stick segmentation. More...
|
|
class | SampleConsensusPrerejective |
| Pose estimation and alignment class using a prerejective RANSAC routine. More...
|
|
class | SamplingSurfaceNormal |
| SamplingSurfaceNormal divides the input space into grids until each grid contains a maximum of N points, and samples points randomly within each grid. More...
|
|
class | ScaledMultiChannel2DComparisonFeatureHandler |
| Feature utility class that handles the creation and evaluation of RGBD comparison features. More...
|
|
class | ScaledMultiChannel2DComparisonFeatureHandlerCCodeGenerator |
|
class | ScopeTime |
| Class to measure the time spent in a scope. More...
|
|
class | SeededHueSegmentation |
| SeededHueSegmentation. 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...
|
|
struct | SetIfFieldExists |
| A helper functor that can set a specific value in a field if the field exists. More...
|
|
class | ShadowPoints |
| ShadowPoints removes the ghost points appearing on edge discontinuties More...
|
|
struct | ShapeContext1980 |
| A point structure representing a Shape Context. More...
|
|
class | ShapeContext3DEstimation |
| ShapeContext3DEstimation implements the 3D shape context descriptor as described in: More...
|
|
struct | SHOT1344 |
| A point structure representing the generic Signature of Histograms of OrienTations (SHOT) - shape+color. More...
|
|
struct | SHOT352 |
| A point structure representing the generic Signature of Histograms of OrienTations (SHOT) - shape only. More...
|
|
class | SHOTColorEstimation |
| SHOTColorEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points, normals and colors. More...
|
|
class | SHOTColorEstimationOMP |
| SHOTColorEstimationOMP estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points, normals and colors, in parallel, using the OpenMP standard. 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 | SHOTEstimationBase |
| SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals. More...
|
|
class | SHOTEstimationOMP |
| SHOTEstimationOMP 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 | SHOTLocalReferenceFrameEstimation |
| SHOTLocalReferenceFrameEstimation estimates the Local Reference Frame used in the calculation of the (SHOT) descriptor. More...
|
|
class | SHOTLocalReferenceFrameEstimationOMP |
| SHOTLocalReferenceFrameEstimation estimates the Local Reference Frame used in the calculation of the (SHOT) descriptor. More...
|
|
class | SIFTKeypoint |
| SIFTKeypoint detects the Scale Invariant Feature Transform keypoints for a given point cloud dataset containing points and intensity. More...
|
|
struct | SIFTKeypointFieldSelector |
|
struct | SIFTKeypointFieldSelector< PointNormal > |
|
struct | SIFTKeypointFieldSelector< PointXYZRGB > |
|
struct | SIFTKeypointFieldSelector< PointXYZRGBA > |
|
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 | SolverDidntConvergeException |
| An exception that is thrown when the non linear solver didn't converge. More...
|
|
struct | SparseQuantizedMultiModTemplate |
| A multi-modality template constructed from a set of quantized multi-modality features. More...
|
|
class | SpinImageEstimation |
| Estimates spin-image descriptors in the given input points. More...
|
|
class | StaticRangeCoder |
| StaticRangeCoder compression class More...
|
|
class | StatisticalMultiscaleInterestRegionExtraction |
| Class for extracting interest regions from unstructured point clouds, based on a multi scale statistical approach. More...
|
|
class | StatisticalOutlierRemoval |
| StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. More...
|
|
class | StatisticalOutlierRemoval< pcl::PCLPointCloud2 > |
| StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. More...
|
|
class | StatsEstimator |
| Class interface for gathering statistics for decision tree learning. More...
|
|
class | StereoGrabber |
|
class | StereoGrabberBase |
| Base class for Stereo file grabber. More...
|
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class | StereoMatching |
| Stereo Matching abstract class. More...
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class | StopWatch |
| Simple stopwatch. More...
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class | Supervoxel |
| Supervoxel container class - stores a cluster extracted using supervoxel clustering. More...
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class | SupervoxelClustering |
| Implements a supervoxel algorithm based on voxel structure, normals, and rgb values. More...
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class | SurfaceNormalModality |
| Modality based on surface normals. More...
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class | SurfaceReconstruction |
| SurfaceReconstruction represents a base surface reconstruction class. More...
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class | SurfelSmoothing |
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class | SUSANKeypoint |
| SUSANKeypoint implements a RGB-D extension of the SUSAN detector including normal directions variation in top of intensity variation. More...
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class | SVM |
| Base class for SVM SVM (Support Vector Machines). More...
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class | SVMClassify |
| SVM (Support Vector Machines) classification of a dataset. More...
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struct | SVMData |
| The structure stores the features and the label of a single sample which has to be used for the training or the classification of the SVM (Support Vector Machines). More...
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struct | SVMDataPoint |
| The structure initialize a single feature value for the classification using SVM (Support Vector Machines). More...
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struct | SVMModel |
| The structure initialize a model created by the SVM (Support Vector Machines) classifier (pcl::SVMTrain). More...
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struct | SVMParam |
| The structure stores the parameters for the classificationa nd must be initialized and passed to the training method pcl::SVMTrain. More...
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class | SVMTrain |
| SVM (Support Vector Machines) training class for the SVM machine learning. More...
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class | SynchronizedQueue |
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class | Synchronizer |
| /brief This template class synchronizes two data streams of different types. More...
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class | TernaryTreeMissingDataBranchEstimator |
| Branch estimator for ternary trees where one branch is used for missing data (indicated by flag != 0). More...
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struct | TexMaterial |
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class | TextureMapping |
| The texture mapping algorithm. More...
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struct | TextureMesh |
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class | TfQuadraticXYZComparison |
| A comparison whether the (x,y,z) components of a given point satisfy (p'Ap + 2v'p + c [OP] 0). More...
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class | TimeTrigger |
| Timer class that invokes registered callback methods periodically. More...
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class | TrajkovicKeypoint2D |
| TrajkovicKeypoint2D implements Trajkovic and Hedley corner detector on organized pooint cloud using intensity information. More...
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class | TrajkovicKeypoint3D |
| TrajkovicKeypoint3D implements Trajkovic and Hedley corner detector on point cloud using geometric information. More...
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class | TransformationFromCorrespondences |
| Calculates a transformation based on corresponding 3D points. More...
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class | TSDFVolume |
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class | UnaryClassifier |
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class | UnhandledPointTypeException |
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class | UniformSampling |
| UniformSampling assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
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class | UniqueShapeContext |
| UniqueShapeContext implements the Unique Shape Context Descriptor described here: More...
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struct | UniqueShapeContext1960 |
| A point structure representing a Unique Shape Context. More...
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class | UnorganizedPointCloudException |
| An exception that is thrown when an organized point cloud is needed but not provided. More...
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class | VectorAverage |
| Calculates the weighted average and the covariance matrix. More...
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struct | Vertices |
| Describes a set of vertices in a polygon mesh, by basically storing an array of indices. More...
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class | VFHEstimation |
| VFHEstimation estimates the Viewpoint Feature Histogram (VFH) descriptor for a given point cloud dataset containing points and normals. More...
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struct | VFHSignature308 |
| A point structure representing the Viewpoint Feature Histogram (VFH). More...
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class | VLPGrabber |
| Grabber for the Velodyne LiDAR (VLP), based on the Velodyne High Definition Laser (HDL) More...
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class | VoxelGrid |
| VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
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class | VoxelGrid< pcl::PCLPointCloud2 > |
| VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
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class | VoxelGridCovariance |
| A searchable voxel strucure containing the mean and covariance of the data. More...
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class | VoxelGridLabel |
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class | VoxelGridOcclusionEstimation |
| VoxelGrid to estimate occluded space in the scene. More...
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class | VTKUtils |
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struct | xNdCopyEigenPointFunctor |
| Helper functor structure for copying data between an Eigen::VectorXf and a PointT. More...
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struct | xNdCopyPointEigenFunctor |
| Helper functor structure for copying data between an Eigen::VectorXf and a PointT. More...
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float | rad2deg (float alpha) |
| Convert an angle from radians to degrees. More...
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float | deg2rad (float alpha) |
| Convert an angle from degrees to radians. More...
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double | rad2deg (double alpha) |
| Convert an angle from radians to degrees. More...
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double | deg2rad (double alpha) |
| Convert an angle from degrees to radians. More...
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float | normAngle (float alpha) |
| Normalize an angle to (-PI, PI]. More...
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template<typename real > |
std::ostream & | operator<< (std::ostream &os, const BivariatePolynomialT< real > &p) |
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template<typename PointT , typename Scalar > |
unsigned int | compute3DCentroid (ConstCloudIterator< PointT > &cloud_iterator, Eigen::Matrix< Scalar, 4, 1 > ¢roid) |
| Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector. More...
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template<typename PointT > |
unsigned int | compute3DCentroid (ConstCloudIterator< PointT > &cloud_iterator, Eigen::Vector4f ¢roid) |
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template<typename PointT > |
unsigned int | compute3DCentroid (ConstCloudIterator< PointT > &cloud_iterator, Eigen::Vector4d ¢roid) |
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template<typename PointT , typename Scalar > |
unsigned int | compute3DCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, 4, 1 > ¢roid) |
| Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector. More...
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template<typename PointT > |
unsigned int | compute3DCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f ¢roid) |
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template<typename PointT > |
unsigned int | compute3DCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4d ¢roid) |
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template<typename PointT , typename Scalar > |
unsigned int | compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix< Scalar, 4, 1 > ¢roid) |
| Compute the 3D (X-Y-Z) centroid of a set of points using their indices and return it as a 3D vector. More...
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template<typename PointT > |
unsigned int | compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Vector4f ¢roid) |
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template<typename PointT > |
unsigned int | compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Vector4d ¢roid) |
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template<typename PointT , typename Scalar > |
unsigned int | compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix< Scalar, 4, 1 > ¢roid) |
| Compute the 3D (X-Y-Z) centroid of a set of points using their indices and return it as a 3D vector. More...
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template<typename PointT > |
unsigned int | compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Vector4f ¢roid) |
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template<typename PointT > |
unsigned int | compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Vector4d ¢roid) |
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template<typename PointT , typename Scalar > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix) |
| Compute the 3x3 covariance matrix of a given set of points. More...
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template<typename PointT > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4f ¢roid, Eigen::Matrix3f &covariance_matrix) |
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template<typename PointT > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4d ¢roid, Eigen::Matrix3d &covariance_matrix) |
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template<typename PointT , typename Scalar > |
unsigned int | computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix) |
| Compute normalized the 3x3 covariance matrix of a given set of points. More...
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template<typename PointT > |
unsigned int | computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4f ¢roid, Eigen::Matrix3f &covariance_matrix) |
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template<typename PointT > |
unsigned int | computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4d ¢roid, Eigen::Matrix3d &covariance_matrix) |
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template<typename PointT , typename Scalar > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix) |
| Compute the 3x3 covariance matrix of a given set of points using their indices. More...
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template<typename PointT > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, const Eigen::Vector4f ¢roid, Eigen::Matrix3f &covariance_matrix) |
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template<typename PointT > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, const Eigen::Vector4d ¢roid, Eigen::Matrix3d &covariance_matrix) |
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template<typename PointT , typename Scalar > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix) |
| Compute the 3x3 covariance matrix of a given set of points using their indices. More...
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template<typename PointT > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4f ¢roid, Eigen::Matrix3f &covariance_matrix) |
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template<typename PointT > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4d ¢roid, Eigen::Matrix3d &covariance_matrix) |
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template<typename PointT , typename Scalar > |
unsigned int | computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Indices &indices, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix) |
| Compute the normalized 3x3 covariance matrix of a given set of points using their indices. More...
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template<typename PointT > |
unsigned int | computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Indices &indices, const Eigen::Vector4f ¢roid, Eigen::Matrix3f &covariance_matrix) |
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template<typename PointT > |
unsigned int | computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Indices &indices, const Eigen::Vector4d ¢roid, Eigen::Matrix3d &covariance_matrix) |
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template<typename PointT , typename Scalar > |
unsigned int | computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix) |
| Compute the normalized 3x3 covariance matrix of a given set of points using their indices. More...
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template<typename PointT > |
unsigned int | computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4f ¢roid, Eigen::Matrix3f &covariance_matrix) |
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template<typename PointT > |
unsigned int | computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4d ¢roid, Eigen::Matrix3d &covariance_matrix) |
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template<typename PointT , typename Scalar > |
unsigned int | computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix, Eigen::Matrix< Scalar, 4, 1 > ¢roid) |
| Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop. More...
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template<typename PointT > |
unsigned int | computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3f &covariance_matrix, Eigen::Vector4f ¢roid) |
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template<typename PointT > |
unsigned int | computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3d &covariance_matrix, Eigen::Vector4d ¢roid) |
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template<typename PointT , typename Scalar > |
unsigned int | computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix, Eigen::Matrix< Scalar, 4, 1 > ¢roid) |
| Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop. More...
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template<typename PointT > |
unsigned int | computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix3f &covariance_matrix, Eigen::Vector4f ¢roid) |
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template<typename PointT > |
unsigned int | computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix3d &covariance_matrix, Eigen::Vector4d ¢roid) |
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template<typename PointT , typename Scalar > |
unsigned int | computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix, Eigen::Matrix< Scalar, 4, 1 > ¢roid) |
| Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop. More...
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template<typename PointT > |
unsigned int | computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3f &covariance_matrix, Eigen::Vector4f ¢roid) |
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template<typename PointT > |
unsigned int | computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3d &covariance_matrix, Eigen::Vector4d ¢roid) |
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template<typename PointT , typename Scalar > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix) |
| Compute the normalized 3x3 covariance matrix for a already demeaned point cloud. More...
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template<typename PointT > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3f &covariance_matrix) |
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template<typename PointT > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3d &covariance_matrix) |
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template<typename PointT , typename Scalar > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix) |
| Compute the normalized 3x3 covariance matrix for a already demeaned point cloud. More...
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template<typename PointT > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix3f &covariance_matrix) |
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template<typename PointT > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix3d &covariance_matrix) |
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template<typename PointT , typename Scalar > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix) |
| Compute the normalized 3x3 covariance matrix for a already demeaned point cloud. More...
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template<typename PointT > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3f &covariance_matrix) |
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template<typename PointT > |
unsigned int | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3d &covariance_matrix) |
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template<typename PointT , typename Scalar > |
void | demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, pcl::PointCloud< PointT > &cloud_out, int npts=0) |
| Subtract a centroid from a point cloud and return the de-meaned representation. More...
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template<typename PointT > |
void | demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4f ¢roid, pcl::PointCloud< PointT > &cloud_out, int npts=0) |
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template<typename PointT > |
void | demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4d ¢roid, pcl::PointCloud< PointT > &cloud_out, int npts=0) |
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template<typename PointT , typename Scalar > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, pcl::PointCloud< PointT > &cloud_out) |
| Subtract a centroid from a point cloud and return the de-meaned representation. More...
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template<typename PointT > |
void | demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4f ¢roid, pcl::PointCloud< PointT > &cloud_out) |
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template<typename PointT > |
void | demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4d ¢roid, pcl::PointCloud< PointT > &cloud_out) |
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template<typename PointT , typename Scalar > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, pcl::PointCloud< PointT > &cloud_out) |
| Subtract a centroid from a point cloud and return the de-meaned representation. More...
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template<typename PointT > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, const Eigen::Vector4f ¢roid, pcl::PointCloud< PointT > &cloud_out) |
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template<typename PointT > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, const Eigen::Vector4d ¢roid, pcl::PointCloud< PointT > &cloud_out) |
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template<typename PointT , typename Scalar > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, pcl::PointCloud< PointT > &cloud_out) |
| Subtract a centroid from a point cloud and return the de-meaned representation. More...
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template<typename PointT > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Vector4f ¢roid, pcl::PointCloud< PointT > &cloud_out) |
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template<typename PointT > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Vector4d ¢roid, pcl::PointCloud< PointT > &cloud_out) |
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template<typename PointT , typename Scalar > |
void | demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_out, int npts=0) |
| Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. More...
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template<typename PointT > |
void | demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4f ¢roid, Eigen::MatrixXf &cloud_out, int npts=0) |
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template<typename PointT > |
void | demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4d ¢roid, Eigen::MatrixXd &cloud_out, int npts=0) |
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template<typename PointT , typename Scalar > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_out) |
| Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. More...
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template<typename PointT > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Vector4f ¢roid, Eigen::MatrixXf &cloud_out) |
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template<typename PointT > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Vector4d ¢roid, Eigen::MatrixXd &cloud_out) |
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template<typename PointT , typename Scalar > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_out) |
| Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. More...
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template<typename PointT > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, const Eigen::Vector4f ¢roid, Eigen::MatrixXf &cloud_out) |
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template<typename PointT > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, const Eigen::Vector4d ¢roid, Eigen::MatrixXd &cloud_out) |
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template<typename PointT , typename Scalar > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_out) |
| Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. More...
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template<typename PointT > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Vector4f ¢roid, Eigen::MatrixXf &cloud_out) |
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template<typename PointT > |
void | demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Vector4d ¢roid, Eigen::MatrixXd &cloud_out) |
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template<typename PointT , typename Scalar > |
void | computeNDCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > ¢roid) |
| General, all purpose nD centroid estimation for a set of points using their indices. More...
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template<typename PointT > |
void | computeNDCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::VectorXf ¢roid) |
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template<typename PointT > |
void | computeNDCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::VectorXd ¢roid) |
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template<typename PointT , typename Scalar > |
void | computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > ¢roid) |
| General, all purpose nD centroid estimation for a set of points using their indices. More...
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template<typename PointT > |
void | computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::VectorXf ¢roid) |
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template<typename PointT > |
void | computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const Indices &indices, Eigen::VectorXd ¢roid) |
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template<typename PointT , typename Scalar > |
void | computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > ¢roid) |
| General, all purpose nD centroid estimation for a set of points using their indices. More...
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template<typename PointT > |
void | computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::VectorXf ¢roid) |
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template<typename PointT > |
void | computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::VectorXd ¢roid) |
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template<typename PointInT , typename PointOutT > |
std::size_t | computeCentroid (const pcl::PointCloud< PointInT > &cloud, PointOutT ¢roid) |
| Compute the centroid of a set of points and return it as a point. More...
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template<typename PointInT , typename PointOutT > |
std::size_t | computeCentroid (const pcl::PointCloud< PointInT > &cloud, const Indices &indices, PointOutT ¢roid) |
| Compute the centroid of a set of points and return it as a point. More...
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PCL_EXPORTS RGB | getRandomColor (double min=0.2, double max=2.8) |
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double | getAngle3D (const Eigen::Vector4f &v1, const Eigen::Vector4f &v2, const bool in_degree=false) |
| Compute the smallest angle between two 3D vectors in radians (default) or degree. More...
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double | getAngle3D (const Eigen::Vector3f &v1, const Eigen::Vector3f &v2, const bool in_degree=false) |
| Compute the smallest angle between two 3D vectors in radians (default) or degree. More...
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void | getMeanStd (const std::vector< float > &values, double &mean, double &stddev) |
| Compute both the mean and the standard deviation of an array of values. More...
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template<typename PointT > |
void | getPointsInBox (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, Indices &indices) |
| Get a set of points residing in a box given its bounds. More...
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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. More...
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template<typename PointT > |
void | getMaxDistance (const pcl::PointCloud< PointT > &cloud, const Indices &indices, const Eigen::Vector4f &pivot_pt, Eigen::Vector4f &max_pt) |
| Get the point at maximum distance from a given point and a given pointcloud. More...
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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. More...
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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. More...
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template<typename PointT > |
void | getMinMax3D (const pcl::PointCloud< PointT > &cloud, const Indices &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. More...
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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. More...
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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. More...
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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. More...
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template<typename PointT > |
float | calculatePolygonArea (const pcl::PointCloud< PointT > &polygon) |
| Calculate the area of a polygon given a point cloud that defines the polygon. More...
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PCL_EXPORTS void | getMinMax (const pcl::PCLPointCloud2 &cloud, int idx, const std::string &field_name, float &min_p, float &max_p) |
| Get the minimum and maximum values on a point histogram. More...
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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. More...
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template<typename PointInT , typename PointOutT > |
void | copyPoint (const PointInT &point_in, PointOutT &point_out) |
| Copy the fields of a source point into a target point. More...
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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. More...
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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) More...
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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) More...
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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. More...
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template<typename PointT > |
double | getMaxSegment (const pcl::PointCloud< PointT > &cloud, const Indices &indices, PointT &pmin, PointT &pmax) |
| Obtain the maximum segment in a given set of points, and return the minimum and maximum points. More...
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template<typename PointType1 , typename PointType2 > |
float | squaredEuclideanDistance (const PointType1 &p1, const PointType2 &p2) |
| Calculate the squared euclidean distance between the two given points. More...
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template<> |
float | squaredEuclideanDistance (const PointXY &p1, const PointXY &p2) |
| Calculate the squared euclidean distance between the two given points. More...
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template<typename PointType1 , typename PointType2 > |
float | euclideanDistance (const PointType1 &p1, const PointType2 &p2) |
| Calculate the euclidean distance between the two given points. More...
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template<typename Scalar , typename Roots > |
void | computeRoots2 (const Scalar &b, const Scalar &c, Roots &roots) |
| Compute the roots of a quadratic polynom x^2 + b*x + c = 0. More...
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template<typename Matrix , typename Roots > |
void | computeRoots (const Matrix &m, Roots &roots) |
| computes the roots of the characteristic polynomial of the input matrix m, which are the eigenvalues More...
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template<typename Matrix , typename Vector > |
void | eigen22 (const Matrix &mat, typename Matrix::Scalar &eigenvalue, Vector &eigenvector) |
| determine the smallest eigenvalue and its corresponding eigenvector More...
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template<typename Matrix , typename Vector > |
void | eigen22 (const Matrix &mat, Matrix &eigenvectors, Vector &eigenvalues) |
| determine the smallest eigenvalue and its corresponding eigenvector More...
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template<typename Matrix , typename Vector > |
void | computeCorrespondingEigenVector (const Matrix &mat, const typename Matrix::Scalar &eigenvalue, Vector &eigenvector) |
| determines the corresponding eigenvector to the given eigenvalue of the symmetric positive semi definite input matrix More...
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template<typename Matrix , typename Vector > |
void | eigen33 (const Matrix &mat, typename Matrix::Scalar &eigenvalue, Vector &eigenvector) |
| determines the eigenvector and eigenvalue of the smallest eigenvalue of the symmetric positive semi definite input matrix More...
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template<typename Matrix , typename Vector > |
void | eigen33 (const Matrix &mat, Vector &evals) |
| determines the eigenvalues of the symmetric positive semi definite input matrix More...
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template<typename Matrix , typename Vector > |
void | eigen33 (const Matrix &mat, Matrix &evecs, Vector &evals) |
| determines the eigenvalues and corresponding eigenvectors of the symmetric positive semi definite input matrix More...
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template<typename Matrix > |
Matrix::Scalar | invert2x2 (const Matrix &matrix, Matrix &inverse) |
| Calculate the inverse of a 2x2 matrix. More...
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template<typename Matrix > |
Matrix::Scalar | invert3x3SymMatrix (const Matrix &matrix, Matrix &inverse) |
| Calculate the inverse of a 3x3 symmetric matrix. More...
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template<typename Matrix > |
Matrix::Scalar | invert3x3Matrix (const Matrix &matrix, Matrix &inverse) |
| Calculate the inverse of a general 3x3 matrix. More...
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template<typename Matrix > |
Matrix::Scalar | determinant3x3Matrix (const Matrix &matrix) |
| Calculate the determinant of a 3x3 matrix. More...
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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) More...
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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) More...
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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) More...
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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) More...
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void | getTransformationFromTwoUnitVectors (const Eigen::Vector3f &y_direction, const Eigen::Vector3f &z_axis, 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) More...
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Eigen::Affine3f | getTransformationFromTwoUnitVectors (const Eigen::Vector3f &y_direction, const Eigen::Vector3f &z_axis) |
| 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) More...
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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 origin 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) More...
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template<typename Scalar > |
void | getEulerAngles (const Eigen::Transform< Scalar, 3, Eigen::Affine > &t, Scalar &roll, Scalar &pitch, Scalar &yaw) |
| Extract the Euler angles (XYZ-convention) from the given transformation. More...
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void | getEulerAngles (const Eigen::Affine3f &t, float &roll, float &pitch, float &yaw) |
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void | getEulerAngles (const Eigen::Affine3d &t, double &roll, double &pitch, double &yaw) |
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template<typename Scalar > |
void | getTranslationAndEulerAngles (const Eigen::Transform< Scalar, 3, Eigen::Affine > &t, Scalar &x, Scalar &y, Scalar &z, Scalar &roll, Scalar &pitch, Scalar &yaw) |
| Extract x,y,z and the Euler angles (XYZ-convention) from the given transformation. More...
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void | getTranslationAndEulerAngles (const Eigen::Affine3f &t, float &x, float &y, float &z, float &roll, float &pitch, float &yaw) |
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void | getTranslationAndEulerAngles (const Eigen::Affine3d &t, double &x, double &y, double &z, double &roll, double &pitch, double &yaw) |
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template<typename Scalar > |
void | getTransformation (Scalar x, Scalar y, Scalar z, Scalar roll, Scalar pitch, Scalar yaw, Eigen::Transform< Scalar, 3, Eigen::Affine > &t) |
| Create a transformation from the given translation and Euler angles (XYZ-convention) More...
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void | getTransformation (float x, float y, float z, float roll, float pitch, float yaw, Eigen::Affine3f &t) |
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void | getTransformation (double x, double y, double z, double roll, double pitch, double yaw, Eigen::Affine3d &t) |
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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) More...
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template<typename Derived > |
void | saveBinary (const Eigen::MatrixBase< Derived > &matrix, std::ostream &file) |
| Write a matrix to an output stream. More...
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template<typename Derived > |
void | loadBinary (Eigen::MatrixBase< Derived > const &matrix, std::istream &file) |
| Read a matrix from an input stream. More...
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template<typename Derived , typename OtherDerived > |
Eigen::internal::umeyama_transform_matrix_type< Derived, OtherDerived >::type | umeyama (const Eigen::MatrixBase< Derived > &src, const Eigen::MatrixBase< OtherDerived > &dst, bool with_scaling=false) |
| Returns the transformation between two point sets. More...
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template<typename Scalar > |
void | transformPoint (const Eigen::Matrix< Scalar, 3, 1 > &point_in, Eigen::Matrix< Scalar, 3, 1 > &point_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation) |
| Transform a point using an affine matrix. More...
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void | transformPoint (const Eigen::Vector3f &point_in, Eigen::Vector3f &point_out, const Eigen::Affine3f &transformation) |
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void | transformPoint (const Eigen::Vector3d &point_in, Eigen::Vector3d &point_out, const Eigen::Affine3d &transformation) |
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template<typename Scalar > |
void | transformVector (const Eigen::Matrix< Scalar, 3, 1 > &vector_in, Eigen::Matrix< Scalar, 3, 1 > &vector_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation) |
| Transform a vector using an affine matrix. More...
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void | transformVector (const Eigen::Vector3f &vector_in, Eigen::Vector3f &vector_out, const Eigen::Affine3f &transformation) |
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void | transformVector (const Eigen::Vector3d &vector_in, Eigen::Vector3d &vector_out, const Eigen::Affine3d &transformation) |
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template<typename Scalar > |
bool | transformLine (const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line_in, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation) |
| Transform a line using an affine matrix. More...
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bool | transformLine (const Eigen::VectorXf &line_in, Eigen::VectorXf &line_out, const Eigen::Affine3f &transformation) |
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bool | transformLine (const Eigen::VectorXd &line_in, Eigen::VectorXd &line_out, const Eigen::Affine3d &transformation) |
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template<typename Scalar > |
void | transformPlane (const Eigen::Matrix< Scalar, 4, 1 > &plane_in, Eigen::Matrix< Scalar, 4, 1 > &plane_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation) |
| Transform plane vectors using an affine matrix. More...
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void | transformPlane (const Eigen::Matrix< double, 4, 1 > &plane_in, Eigen::Matrix< double, 4, 1 > &plane_out, const Eigen::Transform< double, 3, Eigen::Affine > &transformation) |
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void | transformPlane (const Eigen::Matrix< float, 4, 1 > &plane_in, Eigen::Matrix< float, 4, 1 > &plane_out, const Eigen::Transform< float, 3, Eigen::Affine > &transformation) |
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template<typename Scalar > |
void | transformPlane (const pcl::ModelCoefficients::ConstPtr plane_in, pcl::ModelCoefficients::Ptr plane_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation) |
| Transform plane vectors using an affine matrix. More...
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void | transformPlane (const pcl::ModelCoefficients::ConstPtr plane_in, pcl::ModelCoefficients::Ptr plane_out, const Eigen::Transform< double, 3, Eigen::Affine > &transformation) |
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void | transformPlane (const pcl::ModelCoefficients::ConstPtr plane_in, pcl::ModelCoefficients::Ptr plane_out, const Eigen::Transform< float, 3, Eigen::Affine > &transformation) |
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template<typename Scalar > |
bool | checkCoordinateSystem (const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line_x, const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line_y, const Scalar norm_limit=1e-3, const Scalar dot_limit=1e-3) |
| Check coordinate system integrity. More...
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bool | checkCoordinateSystem (const Eigen::Matrix< double, Eigen::Dynamic, 1 > &line_x, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &line_y, const double norm_limit=1e-3, const double dot_limit=1e-3) |
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bool | checkCoordinateSystem (const Eigen::Matrix< float, Eigen::Dynamic, 1 > &line_x, const Eigen::Matrix< float, Eigen::Dynamic, 1 > &line_y, const float norm_limit=1e-3, const float dot_limit=1e-3) |
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template<typename Scalar > |
bool | checkCoordinateSystem (const Eigen::Matrix< Scalar, 3, 1 > &origin, const Eigen::Matrix< Scalar, 3, 1 > &x_direction, const Eigen::Matrix< Scalar, 3, 1 > &y_direction, const Scalar norm_limit=1e-3, const Scalar dot_limit=1e-3) |
| Check coordinate system integrity. More...
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bool | checkCoordinateSystem (const Eigen::Matrix< double, 3, 1 > &origin, const Eigen::Matrix< double, 3, 1 > &x_direction, const Eigen::Matrix< double, 3, 1 > &y_direction, const double norm_limit=1e-3, const double dot_limit=1e-3) |
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bool | checkCoordinateSystem (const Eigen::Matrix< float, 3, 1 > &origin, const Eigen::Matrix< float, 3, 1 > &x_direction, const Eigen::Matrix< float, 3, 1 > &y_direction, const float norm_limit=1e-3, const float dot_limit=1e-3) |
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template<typename Scalar > |
bool | transformBetween2CoordinateSystems (const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > from_line_x, const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > from_line_y, const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > to_line_x, const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > to_line_y, Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation) |
| Compute the transformation between two coordinate systems. More...
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bool | transformBetween2CoordinateSystems (const Eigen::Matrix< double, Eigen::Dynamic, 1 > from_line_x, const Eigen::Matrix< double, Eigen::Dynamic, 1 > from_line_y, const Eigen::Matrix< double, Eigen::Dynamic, 1 > to_line_x, const Eigen::Matrix< double, Eigen::Dynamic, 1 > to_line_y, Eigen::Transform< double, 3, Eigen::Affine > &transformation) |
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bool | transformBetween2CoordinateSystems (const Eigen::Matrix< float, Eigen::Dynamic, 1 > from_line_x, const Eigen::Matrix< float, Eigen::Dynamic, 1 > from_line_y, const Eigen::Matrix< float, Eigen::Dynamic, 1 > to_line_x, const Eigen::Matrix< float, Eigen::Dynamic, 1 > to_line_y, Eigen::Transform< float, 3, Eigen::Affine > &transformation) |
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void | getAllPcdFilesInDirectory (const std::string &directory, std::vector< std::string > &file_names) |
| Find all *.pcd files in the directory and return them sorted. More...
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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 '/') More...
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std::string | getFilenameWithoutExtension (const std::string &input) |
| Remove the extension from the given string and return only the filename (everything before the last '. More...
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std::string | getFileExtension (const std::string &input) |
| Get the file extension from the given string (the remaining string after the last '. More...
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template<typename PointT , typename Scalar > |
unsigned | computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Eigen::Matrix< Scalar, 4, 1 > ¢roid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix) |
| Compute the 3x3 covariance matrix of a given set of points. More...
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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. More...
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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. More...
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template<typename Scalar > |
bool | planeWithPlaneIntersection (const Eigen::Matrix< Scalar, 4, 1 > &plane_a, const Eigen::Matrix< Scalar, 4, 1 > &plane_b, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line, double angular_tolerance) |
| Determine the line of intersection of two non-parallel planes using lagrange multipliers. More...
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template<typename Scalar > |
bool | threePlanesIntersection (const Eigen::Matrix< Scalar, 4, 1 > &plane_a, const Eigen::Matrix< Scalar, 4, 1 > &plane_b, const Eigen::Matrix< Scalar, 4, 1 > &plane_c, Eigen::Matrix< Scalar, 3, 1 > &intersection_point, double determinant_tolerance) |
| Determine the point of intersection of three non-parallel planes by solving the equations. More...
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template<typename PointT > |
int | getFieldIndex (const pcl::PointCloud< PointT > &, const std::string &field_name, std::vector< pcl::PCLPointField > &fields) |
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template<typename PointT > |
int | getFieldIndex (const std::string &field_name, std::vector< pcl::PCLPointField > &fields) |
| Get the index of a specified field (i.e., dimension/channel) More...
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template<typename PointT > |
int | getFieldIndex (const std::string &field_name, const std::vector< pcl::PCLPointField > &fields) |
| Get the index of a specified field (i.e., dimension/channel) More...
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template<typename PointT > |
void | getFields (const pcl::PointCloud< PointT > &, std::vector< pcl::PCLPointField > &fields) |
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template<typename PointT > |
void | getFields (std::vector< pcl::PCLPointField > &fields) |
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template<typename PointT > |
std::vector< pcl::PCLPointField > | getFields () |
| Get the list of available fields (i.e., dimension/channel) More...
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template<typename PointT > |
std::string | getFieldsList (const pcl::PointCloud< PointT > &cloud) |
| Get the list of all fields available in a given cloud. More...
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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. More...
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template<typename PointT , typename IndicesVectorAllocator > |
void | copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, const IndicesAllocator< IndicesVectorAllocator > &indices, pcl::PointCloud< PointT > &cloud_out) |
| Extract the indices of a given point cloud as a new point cloud. More...
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template<typename PointInT , typename PointOutT , typename IndicesVectorAllocator > |
void | copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, const IndicesAllocator< IndicesVectorAllocator > &indices, pcl::PointCloud< PointOutT > &cloud_out) |
| Extract the indices of a given point cloud as a new point cloud. More...
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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. More...
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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. More...
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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. More...
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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. More...
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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. More...
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template<typename PointT > |
void | copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, int top, int bottom, int left, int right, pcl::InterpolationType border_type, const PointT &value) |
| Copy a point cloud inside a larger one interpolating borders. More...
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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. More...
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template<typename FloatVectorT > |
float | L1_Norm (FloatVectorT A, FloatVectorT B, int dim) |
| Compute the L1 norm of the vector between two points. More...
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template<typename FloatVectorT > |
float | L2_Norm_SQR (FloatVectorT A, FloatVectorT B, int dim) |
| Compute the squared L2 norm of the vector between two points. More...
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template<typename FloatVectorT > |
float | L2_Norm (FloatVectorT A, FloatVectorT B, int dim) |
| Compute the L2 norm of the vector between two points. More...
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template<typename FloatVectorT > |
float | Linf_Norm (FloatVectorT A, FloatVectorT B, int dim) |
| Compute the L-infinity norm of the vector between two points. More...
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template<typename FloatVectorT > |
float | JM_Norm (FloatVectorT A, FloatVectorT B, int dim) |
| Compute the JM norm of the vector between two points. More...
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template<typename FloatVectorT > |
float | B_Norm (FloatVectorT A, FloatVectorT B, int dim) |
| Compute the B norm of the vector between two points. More...
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template<typename FloatVectorT > |
float | Sublinear_Norm (FloatVectorT A, FloatVectorT B, int dim) |
| Compute the sublinear norm of the vector between two points. More...
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template<typename FloatVectorT > |
float | CS_Norm (FloatVectorT A, FloatVectorT B, int dim) |
| Compute the CS norm of the vector between two points. More...
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template<typename FloatVectorT > |
float | Div_Norm (FloatVectorT A, FloatVectorT B, int dim) |
| Compute the div norm of the vector between two points. More...
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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. More...
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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. More...
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template<typename FloatVectorT > |
float | KL_Norm (FloatVectorT A, FloatVectorT B, int dim) |
| Compute the KL between two discrete probability density functions. More...
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template<typename FloatVectorT > |
float | HIK_Norm (FloatVectorT A, FloatVectorT B, int dim) |
| Compute the HIK norm of the vector between two points. More...
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template<typename PointT > |
double | estimateProjectionMatrix (typename pcl::PointCloud< PointT >::ConstPtr cloud, Eigen::Matrix< float, 3, 4, Eigen::RowMajor > &projection_matrix, const Indices &indices={}) |
| Estimates the projection matrix P = K * (R|-R*t) from organized point clouds, with K = [[fx, s, cx], [0, fy, cy], [0, 0, 1]] R = rotation matrix and t = translation vector
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template<typename PointT , typename Scalar > |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true) |
| Apply a rigid transform defined by a 4x4 matrix. More...
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template<typename PointT , typename Scalar > |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true) |
| Apply a rigid transform defined by a 4x4 matrix. More...
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template<typename PointT , typename Scalar > |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true) |
| Transform a point cloud and rotate its normals using an Eigen transform. More...
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template<typename PointT , typename Scalar > |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true) |
| Transform a point cloud and rotate its normals using an Eigen transform. More...
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template<typename PointT , typename Scalar > |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 3, 1 > &offset, const Eigen::Quaternion< Scalar > &rotation, bool copy_all_fields=true) |
| Apply a rigid transform defined by a 3D offset and a quaternion. More...
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template<typename PointT , typename Scalar > |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 3, 1 > &offset, const Eigen::Quaternion< Scalar > &rotation, bool copy_all_fields=true) |
| Transform a point cloud and rotate its normals using an Eigen transform. More...
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template<typename PointT , typename Scalar > |
PointT | transformPoint (const PointT &point, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform) |
| Transform a point with members x,y,z. More...
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template<typename PointT , typename Scalar > |
PointT | transformPointWithNormal (const PointT &point, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform) |
| Transform a point with members x,y,z,normal_x,normal_y,normal_z. More...
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template<typename PointT , typename Scalar > |
double | getPrincipalTransformation (const pcl::PointCloud< PointT > &cloud, Eigen::Transform< Scalar, 3, Eigen::Affine > &transform) |
| Calculates the principal (PCA-based) alignment of the point cloud. More...
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template<typename Scalar > |
PCL_EXPORTS bool | planeWithPlaneIntersection (const Eigen::Matrix< Scalar, 4, 1 > &plane_a, const Eigen::Matrix< Scalar, 4, 1 > &plane_b, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line, double angular_tolerance=0.1) |
| Determine the line of intersection of two non-parallel planes using lagrange multipliers. More...
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PCL_EXPORTS bool | planeWithPlaneIntersection (const Eigen::Vector4f &plane_a, const Eigen::Vector4f &plane_b, Eigen::VectorXf &line, double angular_tolerance=0.1) |
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PCL_EXPORTS bool | planeWithPlaneIntersection (const Eigen::Vector4d &plane_a, const Eigen::Vector4d &plane_b, Eigen::VectorXd &line, double angular_tolerance=0.1) |
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template<typename Scalar > |
PCL_EXPORTS bool | threePlanesIntersection (const Eigen::Matrix< Scalar, 4, 1 > &plane_a, const Eigen::Matrix< Scalar, 4, 1 > &plane_b, const Eigen::Matrix< Scalar, 4, 1 > &plane_c, Eigen::Matrix< Scalar, 3, 1 > &intersection_point, double determinant_tolerance=1e-6) |
| Determine the point of intersection of three non-parallel planes by solving the equations. More...
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PCL_EXPORTS bool | threePlanesIntersection (const Eigen::Vector4f &plane_a, const Eigen::Vector4f &plane_b, const Eigen::Vector4f &plane_c, Eigen::Vector3f &intersection_point, double determinant_tolerance=1e-6) |
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PCL_EXPORTS bool | threePlanesIntersection (const Eigen::Vector4d &plane_a, const Eigen::Vector4d &plane_b, const Eigen::Vector4d &plane_c, Eigen::Vector3d &intersection_point, double determinant_tolerance=1e-6) |
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int | getFieldIndex (const pcl::PCLPointCloud2 &cloud, const std::string &field_name) |
| Get the index of a specified field (i.e., dimension/channel) More...
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std::string | getFieldsList (const pcl::PCLPointCloud2 &cloud) |
| Get the available point cloud fields as a space separated string. More...
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int | getFieldSize (const int datatype) |
| Obtains the size of a specific field data type in bytes. More...
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PCL_EXPORTS void | getFieldsSizes (const std::vector< pcl::PCLPointField > &fields, std::vector< int > &field_sizes) |
| Obtain a vector with the sizes of all valid fields (e.g., not "_") More...
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int | getFieldType (const int size, char type) |
| Obtains the type of the PCLPointField from a specific size and type. More...
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char | getFieldType (const int type) |
| Obtains the type of the PCLPointField from a specific PCLPointField as a char. More...
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PCL_EXPORTS int | interpolatePointIndex (int p, int length, InterpolationType type) |
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template<typename PointT > |
PCL_EXPORTS bool | concatenate (const pcl::PointCloud< PointT > &cloud1, const pcl::PointCloud< PointT > &cloud2, pcl::PointCloud< PointT > &cloud_out) |
| Concatenate two pcl::PointCloud<PointT> More...
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PCL_EXPORTS bool | concatenate (const pcl::PCLPointCloud2 &cloud1, const pcl::PCLPointCloud2 &cloud2, pcl::PCLPointCloud2 &cloud_out) |
| Concatenate two pcl::PCLPointCloud2. More...
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PCL_EXPORTS bool | concatenate (const pcl::PolygonMesh &mesh1, const pcl::PolygonMesh &mesh2, pcl::PolygonMesh &mesh_out) |
| Concatenate two pcl::PolygonMesh. More...
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PCL_EXPORTS bool | concatenatePointCloud (const pcl::PCLPointCloud2 &cloud1, const pcl::PCLPointCloud2 &cloud2, pcl::PCLPointCloud2 &cloud_out) |
| Concatenate two pcl::PCLPointCloud2. More...
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PCL_EXPORTS void | copyPointCloud (const pcl::PCLPointCloud2 &cloud_in, const Indices &indices, pcl::PCLPointCloud2 &cloud_out) |
| Extract the indices of a given point cloud as a new point cloud. More...
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PCL_EXPORTS void | copyPointCloud (const pcl::PCLPointCloud2 &cloud_in, const IndicesAllocator< Eigen::aligned_allocator< int > > &indices, pcl::PCLPointCloud2 &cloud_out) |
| Extract the indices of a given point cloud as a new point cloud. More...
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PCL_EXPORTS void | copyPointCloud (const pcl::PCLPointCloud2 &cloud_in, pcl::PCLPointCloud2 &cloud_out) |
| Copy fields and point cloud data from cloud_in to cloud_out. More...
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template<typename Point1T , typename Point2T > |
bool | isSamePointType () |
| Check if two given point types are the same or not. More...
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PCL_EXPORTS bool | concatenateFields (const pcl::PCLPointCloud2 &cloud1_in, const pcl::PCLPointCloud2 &cloud2_in, pcl::PCLPointCloud2 &cloud_out) |
| Concatenate two datasets representing different fields. More...
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PCL_EXPORTS bool | getPointCloudAsEigen (const pcl::PCLPointCloud2 &in, Eigen::MatrixXf &out) |
| Copy the XYZ dimensions of a pcl::PCLPointCloud2 into Eigen format. More...
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PCL_EXPORTS bool | getEigenAsPointCloud (Eigen::MatrixXf &in, pcl::PCLPointCloud2 &out) |
| Copy the XYZ dimensions from an Eigen MatrixXf into a pcl::PCLPointCloud2 message. More...
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template<typename PointT > |
bool | isFinite (const PointT &pt) |
| Tests if the 3D components of a point are all finite param[in] pt point to be tested return true if finite, false otherwise. More...
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template<> |
bool | isFinite< pcl::Axis > (const pcl::Axis &) |
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template<> |
bool | isFinite< pcl::BRISKSignature512 > (const pcl::BRISKSignature512 &) |
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template<> |
bool | isFinite< pcl::BorderDescription > (const pcl::BorderDescription &) |
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template<> |
bool | isFinite< pcl::Boundary > (const pcl::Boundary &) |
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template<> |
bool | isFinite< pcl::ESFSignature640 > (const pcl::ESFSignature640 &) |
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template<> |
bool | isFinite< pcl::FPFHSignature33 > (const pcl::FPFHSignature33 &) |
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template<> |
bool | isFinite< pcl::Intensity > (const pcl::Intensity &) |
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template<> |
bool | isFinite< pcl::IntensityGradient > (const pcl::IntensityGradient &) |
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template<> |
bool | isFinite< pcl::Label > (const pcl::Label &) |
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template<> |
bool | isFinite< pcl::MomentInvariants > (const pcl::MomentInvariants &) |
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template<> |
bool | isFinite< pcl::NormalBasedSignature12 > (const pcl::NormalBasedSignature12 &) |
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template<> |
bool | isFinite< pcl::PFHRGBSignature250 > (const pcl::PFHRGBSignature250 &) |
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template<> |
bool | isFinite< pcl::PFHSignature125 > (const pcl::PFHSignature125 &) |
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template<> |
bool | isFinite< pcl::PPFRGBSignature > (const pcl::PPFRGBSignature &) |
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template<> |
bool | isFinite< pcl::PPFSignature > (const pcl::PPFSignature &) |
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template<> |
bool | isFinite< pcl::PrincipalCurvatures > (const pcl::PrincipalCurvatures &) |
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template<> |
bool | isFinite< pcl::PrincipalRadiiRSD > (const pcl::PrincipalRadiiRSD &) |
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template<> |
bool | isFinite< pcl::RGB > (const pcl::RGB &) |
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template<> |
bool | isFinite< pcl::ReferenceFrame > (const pcl::ReferenceFrame &) |
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template<> |
bool | isFinite< pcl::SHOT1344 > (const pcl::SHOT1344 &) |
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template<> |
bool | isFinite< pcl::SHOT352 > (const pcl::SHOT352 &) |
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template<> |
bool | isFinite< pcl::ShapeContext1980 > (const pcl::ShapeContext1980 &) |
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template<> |
bool | isFinite< pcl::UniqueShapeContext1960 > (const pcl::UniqueShapeContext1960 &) |
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template<> |
bool | isFinite< pcl::VFHSignature308 > (const pcl::VFHSignature308 &) |
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template<> |
bool | isFinite< pcl::PointXY > (const pcl::PointXY &p) |
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template<> |
bool | isFinite< pcl::Normal > (const pcl::Normal &n) |
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template<typename PointT , traits::HasNoXY< PointT > = true> |
constexpr bool | isXYFinite (const PointT &) noexcept |
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template<typename PointT , traits::HasNoXYZ< PointT > = true> |
constexpr bool | isXYZFinite (const PointT &) noexcept |
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template<typename PointT , traits::HasNoNormal< PointT > = true> |
constexpr bool | isNormalFinite (const PointT &) noexcept |
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template<typename PointT , traits::HasXY< PointT > = true> |
bool | isXYFinite (const PointT &pt) noexcept |
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template<typename PointT , traits::HasXYZ< PointT > = true> |
bool | isXYZFinite (const PointT &pt) noexcept |
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template<typename PointT , traits::HasNormal< PointT > = true> |
bool | isNormalFinite (const PointT &pt) noexcept |
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PCL_EXPORTS void | getCameraMatrixFromProjectionMatrix (const Eigen::Matrix< float, 3, 4, Eigen::RowMajor > &projection_matrix, Eigen::Matrix3f &camera_matrix) |
| Determines the camera matrix from the given projection matrix. More...
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double | getTime () |
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template<typename PointT , typename Scalar > |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true) |
| Apply an affine transform defined by an Eigen Transform. More...
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template<typename PointT > |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true) |
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template<typename PointT , typename Scalar > |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true) |
| Apply an affine transform defined by an Eigen Transform. More...
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template<typename PointT > |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true) |
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template<typename PointT , typename Scalar > |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true) |
| Apply an affine transform defined by an Eigen Transform. More...
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template<typename PointT > |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true) |
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template<typename PointT , typename Scalar > |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true) |
| Transform a point cloud and rotate its normals using an Eigen transform. More...
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template<typename PointT > |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true) |
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template<typename PointT , typename Scalar > |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true) |
| Transform a point cloud and rotate its normals using an Eigen transform. More...
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template<typename PointT > |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true) |
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template<typename PointT , typename Scalar > |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true) |
| Transform a point cloud and rotate its normals using an Eigen transform. More...
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template<typename PointT > |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true) |
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template<typename PointT > |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true) |
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template<typename PointT > |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true) |
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template<typename PointT , typename Scalar > |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true) |
| Apply a rigid transform defined by a 4x4 matrix. More...
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template<typename PointT > |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true) |
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template<typename PointT > |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true) |
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template<typename PointT > |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const Indices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true) |
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template<typename PointT , typename Scalar > |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true) |
| Transform a point cloud and rotate its normals using an Eigen transform. More...
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template<typename PointT > |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true) |
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template<typename PointT > |
void | transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Vector3f &offset, const Eigen::Quaternionf &rotation, bool copy_all_fields=true) |
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template<typename PointT > |
void | transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Vector3f &offset, const Eigen::Quaternionf &rotation, bool copy_all_fields=true) |
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template<typename PointT > |
PointT | transformPoint (const PointT &point, const Eigen::Affine3f &transform) |
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template<typename PointT > |
PointT | transformPointWithNormal (const PointT &point, const Eigen::Affine3f &transform) |
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template<typename PointT > |
double | getPrincipalTransformation (const pcl::PointCloud< PointT > &cloud, Eigen::Affine3f &transform) |
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template<typename PointT > |
void | createMapping (const std::vector< pcl::PCLPointField > &msg_fields, MsgFieldMap &field_map) |
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template<typename PointT > |
void | fromPCLPointCloud2 (const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud, const MsgFieldMap &field_map) |
| Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map. More...
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template<typename PointT > |
void | fromPCLPointCloud2 (const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud) |
| Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object. More...
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template<typename PointT > |
void | toPCLPointCloud2 (const pcl::PointCloud< PointT > &cloud, pcl::PCLPointCloud2 &msg) |
| Convert a pcl::PointCloud<T> object to a PCLPointCloud2 binary data blob. More...
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template<typename CloudT > |
void | toPCLPointCloud2 (const CloudT &cloud, pcl::PCLImage &msg) |
| Copy the RGB fields of a PointCloud into pcl::PCLImage format. More...
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void | toPCLPointCloud2 (const pcl::PCLPointCloud2 &cloud, pcl::PCLImage &msg) |
| Copy the RGB fields of a PCLPointCloud2 msg into pcl::PCLImage format. More...
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const Correspondence &c) |
| overloaded << operator More...
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void | getRejectedQueryIndices (const pcl::Correspondences &correspondences_before, const pcl::Correspondences &correspondences_after, Indices &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. More...
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bool | isBetterCorrespondence (const Correspondence &pc1, const Correspondence &pc2) |
| Comparator to enable us to sort a vector of PointCorrespondences according to their scores using std::sort (begin(), end(), isBetterCorrespondence);. More...
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template<typename Sequence , typename F > |
void | for_each_type (F f) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointXYZ &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const RGB &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const Intensity &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const Intensity8u &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const Intensity32u &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointXYZI &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointXYZL &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const Label &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointXYZRGBA &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointXYZRGB &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointXYZRGBL &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointXYZHSV &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointXY &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointUV &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const InterestPoint &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const Normal &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const Axis &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointNormal &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointXYZRGBNormal &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointXYZINormal &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointXYZLNormal &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointWithRange &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointWithViewpoint &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const MomentInvariants &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PrincipalRadiiRSD &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const Boundary &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PrincipalCurvatures &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PFHSignature125 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PFHRGBSignature250 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PPFSignature &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const CPPFSignature &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PPFRGBSignature &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const NormalBasedSignature12 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const ShapeContext1980 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const UniqueShapeContext1960 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const SHOT352 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const SHOT1344 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const ReferenceFrame &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const FPFHSignature33 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const VFHSignature308 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const GRSDSignature21 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const BRISKSignature512 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const ESFSignature640 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const GASDSignature512 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const GASDSignature984 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const GASDSignature7992 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const GFPFHSignature16 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const Narf36 &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const BorderDescription &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const IntensityGradient &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointWithScale &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointSurfel &p) |
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PCL_EXPORTS std::ostream & | operator<< (std::ostream &os, const PointDEM &p) |
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template<int N> |
std::ostream & | operator<< (std::ostream &os, const Histogram< N > &p) |
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template<typename T , typename ... Args> |
shared_ptr< T > | make_shared (Args &&... args) |
| Returns a pcl::shared_ptr compliant with type T's allocation policy. More...
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std::ostream & | operator<< (std::ostream &s, const ::pcl::ModelCoefficients &v) |
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std::ostream & | operator<< (std::ostream &out, const PCLHeader &h) |
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bool | operator== (const PCLHeader &lhs, const PCLHeader &rhs) |
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std::ostream & | operator<< (std::ostream &s, const ::pcl::PCLImage &v) |
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std::ostream & | operator<< (std::ostream &s, const ::pcl::PCLPointCloud2 &v) |
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std::ostream & | operator<< (std::ostream &s, const ::pcl::PCLPointField &v) |
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template<typename PointT > |
std::ostream & | operator<< (std::ostream &s, const pcl::PointCloud< PointT > &p) |
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void | PointXYZRGBtoXYZI (const PointXYZRGB &in, PointXYZI &out) |
| Convert a XYZRGB point type to a XYZI. More...
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void | PointRGBtoI (const RGB &in, Intensity &out) |
| Convert a RGB point type to a I. More...
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void | PointRGBtoI (const RGB &in, Intensity8u &out) |
| Convert a RGB point type to a I. More...
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void | PointRGBtoI (const RGB &in, Intensity32u &out) |
| Convert a RGB point type to a I. More...
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void | PointXYZRGBtoXYZHSV (const PointXYZRGB &in, PointXYZHSV &out) |
| Convert a XYZRGB point type to a XYZHSV. More...
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void | PointXYZRGBAtoXYZHSV (const PointXYZRGBA &in, PointXYZHSV &out) |
| Convert a XYZRGBA point type to a XYZHSV. More...
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void | PointXYZHSVtoXYZRGB (const PointXYZHSV &in, PointXYZRGB &out) |
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void | PointCloudRGBtoI (const PointCloud< RGB > &in, PointCloud< Intensity > &out) |
| Convert a RGB point cloud to an Intensity. More...
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void | PointCloudRGBtoI (const PointCloud< RGB > &in, PointCloud< Intensity8u > &out) |
| Convert a RGB point cloud to an Intensity. More...
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void | PointCloudRGBtoI (const PointCloud< RGB > &in, PointCloud< Intensity32u > &out) |
| Convert a RGB point cloud to an Intensity. More...
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void | PointCloudXYZRGBtoXYZHSV (const PointCloud< PointXYZRGB > &in, PointCloud< PointXYZHSV > &out) |
| Convert a XYZRGB point cloud to a XYZHSV. More...
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void | PointCloudXYZRGBAtoXYZHSV (const PointCloud< PointXYZRGBA > &in, PointCloud< PointXYZHSV > &out) |
| Convert a XYZRGB point cloud to a XYZHSV. More...
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void | PointCloudXYZRGBtoXYZI (const PointCloud< PointXYZRGB > &in, PointCloud< PointXYZI > &out) |
| Convert a XYZRGB point cloud to a XYZI. More...
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void | PointCloudDepthAndRGBtoXYZRGBA (const PointCloud< Intensity > &depth, const PointCloud< RGB > &image, const float &focal, PointCloud< PointXYZRGBA > &out) |
| Convert registered Depth image and RGB image to PointCloudXYZRGBA. More...
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std::ostream & | operator<< (std::ostream &s, const ::pcl::PointIndices &v) |
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std::ostream & | operator<< (std::ostream &s, const ::pcl::PolygonMesh &v) |
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std::ostream & | operator<< (std::ostream &os, const RangeImage &r) |
| /ingroup range_image More...
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template<typename PointT , typename ValT > |
void | setFieldValue (PointT &pt, std::size_t field_offset, const ValT &value) |
| Set the value at a specified field in a point. More...
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template<typename PointT , typename ValT > |
void | getFieldValue (const PointT &pt, std::size_t field_offset, ValT &value) |
| Get the value at a specified field in a point. More...
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std::ostream & | operator<< (std::ostream &s, const ::pcl::Vertices &v) |
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PCL_EXPORTS bool | computeCPPFPairFeature (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4i &c1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, const Eigen::Vector4i &c2, float &f1, float &f2, float &f3, float &f4, float &f5, float &f6, float &f7, float &f8, float &f9, float &f10) |
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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. More...
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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. More...
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std::ostream & | operator<< (std::ostream &os, const RangeImageBorderExtractor::Parameters &p) |
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template<typename PointT > |
bool | 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. More...
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template<typename PointT > |
bool | computePointNormal (const pcl::PointCloud< PointT > &cloud, const pcl::Indices &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. More...
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template<typename PointT , typename Scalar > |
void | flipNormalTowardsViewpoint (const PointT &point, float vp_x, float vp_y, float vp_z, Eigen::Matrix< Scalar, 4, 1 > &normal) |
| Flip (in place) the estimated normal of a point towards a given viewpoint. More...
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template<typename PointT , typename Scalar > |
void | flipNormalTowardsViewpoint (const PointT &point, float vp_x, float vp_y, float vp_z, Eigen::Matrix< Scalar, 3, 1 > &normal) |
| Flip (in place) the estimated normal of a point towards a given viewpoint. More...
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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. More...
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template<typename PointNT > |
bool | flipNormalTowardsNormalsMean (pcl::PointCloud< PointNT > const &normal_cloud, pcl::Indices const &normal_indices, Eigen::Vector3f &normal) |
| Flip (in place) normal to get the same sign of the mean of the normals specified by normal_indices. More...
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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. More...
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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) |
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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) |
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template<int N> |
void | getFeaturePointCloud (const std::vector< Eigen::MatrixXf, Eigen::aligned_allocator< Eigen::MatrixXf > > &histograms2D, PointCloud< Histogram< N > > &histogramsPC) |
| Transform a list of 2D matrices into a point cloud containing the values in a vector (Histogram<N>). More...
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template<typename PointInT , typename PointNT , typename PointOutT > |
Eigen::MatrixXf | computeRSD (const pcl::PointCloud< PointInT > &surface, const pcl::PointCloud< PointNT > &normals, const pcl::Indices &indices, double max_dist, int nr_subdiv, double plane_radius, PointOutT &radii, bool compute_histogram=false) |
| Estimate the Radius-based Surface Descriptor (RSD) for a given point based on its spatial neighborhood of 3D points with normals. More...
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template<typename PointNT , typename PointOutT > |
Eigen::MatrixXf | computeRSD (const pcl::PointCloud< PointNT > &normals, const pcl::Indices &indices, const std::vector< float > &sqr_dists, double max_dist, int nr_subdiv, double plane_radius, PointOutT &radii, bool compute_histogram=false) |
| Estimate the Radius-based Surface Descriptor (RSD) for a given point based on its spatial neighborhood of 3D points with normals. More...
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template<typename PointT > |
void | removeNaNFromPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, Indices &index) |
| Removes points with x, y, or z equal to NaN. More...
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template<typename PointT > |
void | removeNaNNormalsFromPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, Indices &index) |
| Removes points that have their normals invalid (i.e., equal to NaN) More...
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template<typename PointT > |
void | removeNaNFromPointCloud (const pcl::PointCloud< PointT > &cloud_in, Indices &index) |
| Removes points with x, y, or z equal to NaN (dry run). More...
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template<typename PointT > |
void | applyMorphologicalOperator (const typename pcl::PointCloud< PointT >::ConstPtr &cloud_in, float resolution, const int morphological_operator, pcl::PointCloud< PointT > &cloud_out) |
| Apply morphological operator to the z dimension of the input point cloud. More...
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template<typename PointT > |
PCL_EXPORTS void | applyMorphologicalOperator (const typename pcl::PointCloud< PointT >::ConstPtr &cloud_in, float resolution, const int morphological_operator, pcl::PointCloud< PointT > &cloud_out) |
| Apply morphological operator to the z dimension of the input point cloud. More...
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template<typename NormalT > |
std::vector< float > | assignNormalWeights (const PointCloud< NormalT > &cloud, index_t index, const Indices &k_indices, const std::vector< float > &k_sqr_distances) |
| Assign weights of nearby normals used for refinement. More...
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template<typename NormalT > |
bool | refineNormal (const PointCloud< NormalT > &cloud, int index, const Indices &k_indices, const std::vector< float > &k_sqr_distances, NormalT &point) |
| Refine an indexed point based on its neighbors, this function only writes to the normal_* fields. More...
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PCL_EXPORTS void | getMinMax3D (const pcl::PCLPointCloud2ConstPtr &cloud, int x_idx, int y_idx, int z_idx, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt) |
| Obtain the maximum and minimum points in 3D from a given point cloud. More...
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PCL_EXPORTS void | getMinMax3D (const pcl::PCLPointCloud2ConstPtr &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) |
| Obtain the maximum and minimum points in 3D from a given point cloud. More...
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Eigen::MatrixXi | getHalfNeighborCellIndices () |
| Get the relative cell indices of the "upper half" 13 neighbors. More...
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Eigen::MatrixXi | getAllNeighborCellIndices () |
| Get the relative cell indices of all the 26 neighbors. More...
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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. More...
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template<typename PointT > |
void | getMinMax3D (const typename pcl::PointCloud< PointT >::ConstPtr &cloud, const Indices &indices, 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. More...
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template<typename PointT > |
void | approximatePolygon (const PlanarPolygon< PointT > &polygon, PlanarPolygon< PointT > &approx_polygon, float threshold, bool refine=false, bool closed=true) |
| see approximatePolygon2D More...
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template<typename PointT > |
void | approximatePolygon2D (const typename PointCloud< PointT >::VectorType &polygon, typename PointCloud< PointT >::VectorType &approx_polygon, float threshold, bool refine=false, bool closed=true) |
| returns an approximate polygon to given 2D contour. More...
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template<typename Type > |
std::enable_if_t< std::is_floating_point< Type >::value > | copyValueString (const pcl::PCLPointCloud2 &cloud, const pcl::index_t point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream) |
| inserts a value of type Type (uchar, char, uint, int, float, double, ...) into a stringstream. More...
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template<typename Type > |
std::enable_if_t< std::is_integral< Type >::value > | copyValueString (const pcl::PCLPointCloud2 &cloud, const pcl::index_t point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream) |
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template<> |
void | copyValueString< std::int8_t > (const pcl::PCLPointCloud2 &cloud, const pcl::index_t point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream) |
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template<> |
void | copyValueString< std::uint8_t > (const pcl::PCLPointCloud2 &cloud, const pcl::index_t point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream) |
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template<typename Type > |
std::enable_if_t< std::is_floating_point< Type >::value, bool > | isValueFinite (const pcl::PCLPointCloud2 &cloud, const pcl::index_t point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count) |
| Check whether a given value of type Type (uchar, char, uint, int, float, double, ...) is finite or not. More...
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template<typename Type > |
std::enable_if_t< std::is_integral< Type >::value, bool > | isValueFinite (const pcl::PCLPointCloud2 &, const pcl::index_t, const int, const unsigned int, const unsigned int) |
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template<typename Type > |
void | copyStringValue (const std::string &st, pcl::PCLPointCloud2 &cloud, pcl::index_t point_index, unsigned int field_idx, unsigned int fields_count) |
| Copy one single value of type T (uchar, char, uint, int, float, double, ...) from a string. More...
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template<typename Type > |
void | copyStringValue (const std::string &st, pcl::PCLPointCloud2 &cloud, pcl::index_t point_index, unsigned int field_idx, unsigned int fields_count, std::istringstream &is) |
| Copy one single value of type T (uchar, char, uint, int, float, double, ...) from a string. More...
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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. More...
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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. More...
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template<typename PointT > |
void | getApproximateIndices (const typename pcl::PointCloud< PointT >::ConstPtr &cloud_in, const typename pcl::PointCloud< PointT >::ConstPtr &cloud_ref, std::vector< int > &indices) |
| Get a set of approximate indices for a given point cloud into a reference point cloud. More...
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template<typename Point1T , typename Point2T > |
void | getApproximateIndices (const typename pcl::PointCloud< Point1T >::ConstPtr &cloud_in, const typename pcl::PointCloud< Point2T >::ConstPtr &cloud_ref, std::vector< int > &indices) |
| Get a set of approximate indices for a given point cloud into a reference point cloud. More...
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std::ostream & | operator<< (std::ostream &os, const NarfKeypoint::Parameters &p) |
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std::ostream & | operator<< (std::ostream &os, const GradientXY &p) |
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template<class Type > |
void | read (std::istream &stream, Type &value) |
| Function for reading data from a stream. More...
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template<class Type > |
void | read (std::istream &stream, Type *value, int nr_values) |
| Function for reading data arrays from a stream. More...
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template<class Type > |
void | write (std::ostream &stream, Type value) |
| Function for writing data to a stream. More...
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template<class Type > |
void | write (std::ostream &stream, Type *value, int nr_values) |
| Function for writing data arrays to a stream. More...
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template<typename PointT > |
float | getMeanPointDensity (const typename pcl::PointCloud< PointT >::ConstPtr &cloud, float max_dist, int nr_threads=1) |
| Compute the mean point density of a given point cloud. More...
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template<typename PointT > |
float | getMeanPointDensity (const typename pcl::PointCloud< PointT >::ConstPtr &cloud, const std::vector< int > &indices, float max_dist, int nr_threads=1) |
| Compute the mean point density of a given point cloud. More...
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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. More...
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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. More...
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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. More...
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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. More...
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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. More...
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template<typename PointT > |
void | extractEuclideanClusters (const PointCloud< PointT > &cloud, const typename search::Search< PointT >::Ptr &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. More...
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template<typename PointT > |
void | extractEuclideanClusters (const PointCloud< PointT > &cloud, const Indices &indices, const typename search::Search< PointT >::Ptr &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. More...
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template<typename PointT , typename Normal > |
void | extractEuclideanClusters (const PointCloud< PointT > &cloud, const PointCloud< Normal > &normals, float tolerance, const typename KdTree< PointT >::Ptr &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 between points. More...
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template<typename PointT , typename Normal > |
void | extractEuclideanClusters (const PointCloud< PointT > &cloud, const PointCloud< Normal > &normals, const Indices &indices, const typename KdTree< PointT >::Ptr &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 between points. More...
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bool | comparePointClusters (const pcl::PointIndices &a, const pcl::PointIndices &b) |
| Sort clusters method (for std::sort). More...
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template<typename PointT > |
void | extractLabeledEuclideanClusters (const PointCloud< PointT > &cloud, const typename search::Search< PointT >::Ptr &tree, float tolerance, std::vector< std::vector< PointIndices >> &labeled_clusters, unsigned int min_pts_per_cluster, unsigned int max_pts_per_cluster, unsigned int max_label) |
| Decompose a region of space into clusters based on the Euclidean distance between points. More...
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template<typename PointT > |
void | extractLabeledEuclideanClusters (const PointCloud< PointT > &cloud, const typename search::Search< PointT >::Ptr &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< unsigned int >::max()) |
| Decompose a region of space into clusters based on the Euclidean distance between points. More...
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bool | compareLabeledPointClusters (const pcl::PointIndices &a, const pcl::PointIndices &b) |
| Sort clusters method (for std::sort). More...
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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. More...
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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. More...
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template<> |
float | squaredEuclideanDistance (const pcl::segmentation::grabcut::Color &c1, const pcl::segmentation::grabcut::Color &c2) |
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bool | comparePair (std::pair< float, int > i, std::pair< float, int > j) |
| This function is used as a comparator for sorting. More...
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void | seededHueSegmentation (const PointCloud< PointXYZRGB > &cloud, const search::Search< PointXYZRGB >::Ptr &tree, float tolerance, PointIndices &indices_in, PointIndices &indices_out, float delta_hue=0.0) |
| Decompose a region of space into clusters based on the Euclidean distance between points. More...
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void | seededHueSegmentation (const PointCloud< PointXYZRGB > &cloud, const search::Search< PointXYZRGBL >::Ptr &tree, float tolerance, PointIndices &indices_in, PointIndices &indices_out, float delta_hue=0.0) |
| Decompose a region of space into clusters based on the Euclidean distance between points. More...
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template<typename PointT > |
void | getPointCloudDifference (const pcl::PointCloud< PointT > &src, double threshold, const typename pcl::search::Search< PointT >::Ptr &tree, pcl::PointCloud< PointT > &output) |
| Obtain the difference between two aligned point clouds as another point cloud, given a distance threshold. More...
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template<class T > |
short int | doStereoRatioFilter (const T *const acc, short int dbest, T sad_min, int ratio_filter, int maxdisp, int precision=100) |
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template<class T > |
short int | doStereoPeakFilter (const T *const acc, short int dbest, int peak_filter, int maxdisp) |
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bool | comparePoints2D (const std::pair< int, Eigen::Vector4f > &p1, const std::pair< int, Eigen::Vector4f > &p2) |
| Sort 2D points in a vector structure. More...
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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. More...
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