Definition at line 563 of file point_cloud.h. These types should be enough to support all the algorithms and methods implemented in PCL. Some of the clearly stated advantages include: An additional advantage is that by controlling the file format, we can best A point cloud is a data structure used to represent a collection of multi-dimensional points and is commonly used to represent three-dimensional data such as the output of a stereo camera, 3D . That is not specific to organized pointclouds. Definition at line 352 of file point_cloud.h. cloud->points[i].x will give you the x-coordinate. Definition at line 523 of file point_cloud.h. Pages generated on Tue Aug 22 2017 13:03:08, pcl::PointCloud< PointT > Singleton Reference, pcl::FastBilateralFilterOMP< PointT >::applyFilter(), pcl::FrustumCulling< PointT >::applyFilter(), pcl::filters::Pyramid< PointT >::compute(), pcl::occlusion_reasoning::getOccludedCloud(), pcl::VoxelGridCovariance< PointT >::applyFilter(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::getEdgeIndex(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::getFaceIndex(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::getHalfEdgeIndex(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::getVertexIndex(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::cleanUp(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeCovariances(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::extractDescriptors(), pcl::common::CloudGenerator< PointT, GeneratorT >::fill(), pcl::common::CloudGenerator< pcl::PointXY, GeneratorT >::fill(), pcl::SupervoxelClustering< PointT >::getLabeledCloud(), pcl::SupervoxelClustering< PointT >::getLabeledVoxelCloud(), pcl::SupervoxelClustering< PointT >::makeSupervoxelNormalCloud(), pcl::MovingLeastSquares< PointInT, PointOutT >::performProcessing(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::refineCorners(), pcl::LCCPSegmentation< PointT >::relabelCloud(), pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateTransformation(), pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateTransformation(), pcl::DisparityMapConverter< PointT >::compute(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::computeFeature(), pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::computeRFAndShapeDistribution(), pcl::TSDFVolume< VoxelT, WeightT >::convertToTsdfCloud(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::TrajkovicKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::TrajkovicKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::VoxelGridCovariance< PointT >::getDisplayCloud(), pcl::MarchingCubes< PointNT >::performReconstruction(), pcl::SurfaceReconstruction< PointInT >::reconstruct(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseHarris(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseLowe(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseNoble(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseTomasi(), pcl::visualization::ImageViewer::addMask(), pcl::HypothesisVerification< ModelT, SceneT >::addModels(), pcl::visualization::ImageViewer::addPlanarPolygon(), pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::visualization::ImageViewer::addRectangle(), pcl::io::PointCloudImageExtractor< PointT >::extract(), pcl::Edge< PointInT, PointOutT >::canny(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::estimateFeatures(), pcl::Edge< PointInT, PointOutT >::sobelMagnitudeDirection(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::addData(), pcl::MovingLeastSquares< PointInT, PointOutT >::computeMLSPointNormal(), pcl::MarchingCubes< PointNT >::createSurface(), pcl::BriskKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::gpu::extractLabeledEuclideanClusters(), pcl::MovingLeastSquares< PointInT, PointOutT >::performUpsampling(), pcl::OrganizedConnectedComponentSegmentation< PointT, PointLT >::segment(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::setPointsToTrack(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::track(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::computeTracking(), pcl::CovarianceSampling< PointT, PointNT >::applyFilter(), pcl::BRISK2DEstimation< PointInT, PointOutT, KeypointT, IntensityT >::compute(), pcl::LineRGBD< PointXYZT, PointRGBT >::computeTransformedTemplatePoints(), pcl::filters::Convolution3D< PointIn, PointOut, KernelT >::convolve(), pcl::kernel< PointT >::derivativeXBackwardKernel(), pcl::kernel< PointT >::derivativeXCentralKernel(), pcl::kernel< PointT >::derivativeXForwardKernel(), pcl::kernel< PointT >::derivativeYBackwardKernel(), pcl::kernel< PointT >::derivativeYCentralKernel(), pcl::kernel< PointT >::derivativeYForwardKernel(), pcl::Edge< PointInT, PointOutT >::detectEdgeCanny(), pcl::Edge< PointInT, PointOutT >::detectEdgePrewitt(), pcl::Edge< PointInT, PointOutT >::detectEdgeRoberts(), pcl::Edge< PointInT, PointOutT >::detectEdgeSobel(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::Morphology< PointT >::dilationBinary(), pcl::Morphology< PointT >::dilationGray(), pcl::Morphology< PointT >::erosionBinary(), pcl::OrganizedEdgeFromRGB< PointT, PointLT >::extractEdges(), pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::extractEdges(), pcl::filters::Convolution< PointIn, PointOut >::initCompute(), pcl::Morphology< PointT >::intersectionBinary(), pcl::search::Search< PointXYZRGB >::nearestKSearchT(), pcl::BilateralUpsampling< PointInT, PointOutT >::performProcessing(), pcl::Poisson< PointNT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::ColorGradientModality< PointInT >::processInputData(), pcl::search::Search< PointXYZRGB >::radiusSearchT(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseHarris(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseLowe(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseNoble(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseTomasi(), pcl::OrganizedMultiPlaneSegmentation< PointT, PointNT, PointLT >::segment(), pcl::OrganizedMultiPlaneSegmentation< PointT, PointNT, PointLT >::segmentAndRefine(), pcl::Morphology< PointT >::structuringElementCircular(), pcl::Morphology< PointT >::structuringElementRectangle(), pcl::Morphology< PointT >::subtractionBinary(), pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::validateTransformation(), pcl::visualization::PCLVisualizer::addPolygonMesh(), pcl::LineRGBD< PointXYZT, PointRGBT >::addTemplate(), pcl::recognition::TrimmedICP< pcl::pcl::PointXYZ, float >::align(), pcl::PlaneClipper3D< PointT >::clipPointCloud3D(), pcl::BoxClipper3D< PointT >::clipPointCloud3D(), pcl::LineRGBD< PointXYZT, PointRGBT >::createAndAddTemplate(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::derivatives(), pcl::registration::TransformationEstimationPointToPlaneWeighted< PointSource, PointTarget, MatScalar >::estimateRigidTransformation(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::findObjects(), pcl::ISSKeypoint3D< PointInT, PointOutT, NormalT >::getBoundaryPoints(), pcl::LineRGBD< PointXYZT, PointRGBT >::loadTemplates(), pcl::search::Search< PointT >::nearestKSearch(), pcl::search::FlannSearch< PointT, FlannDistance >::nearestKSearch(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::MovingLeastSquares< PointInT, PointOutT >::process(), pcl::search::FlannSearch< PointT, FlannDistance >::radiusSearch(), pcl::search::Search< PointT >::radiusSearch(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::refineCorners(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setEdgeDataCloud(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setFaceDataCloud(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setHalfEdgeDataCloud(), pcl::SupervoxelClustering< PointT >::setInputCloud(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::setInputSource(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setVertexDataCloud(), pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::transformCloud(), pcl::visualization::PCLVisualizer::updatePolygonMesh(), pcl::Registration< PointSource, PointTarget, Scalar >::align(), pcl::ConditionalRemoval< PointT >::applyFilter(), pcl::ESFEstimation< PointInT, PointOutT >::compute(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::compute(), pcl::VFHEstimation< PointInT, PointNT, PointOutT >::compute(), pcl::Feature< PointInT, PointOutT >::compute(), pcl::features::computeApproximateNormals(), pcl::SmoothedSurfacesKeypoint< PointT, PointNT >::detectKeypoints(), pcl::ISSKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::MultiscaleFeaturePersistence< PointSource, PointFeature >::determinePersistentFeatures(), pcl::Filter< pcl::PointXYZRGBL >::filter(), pcl::CloudSurfaceProcessing< PointInT, PointOutT >::process(), pcl::BilateralUpsampling< PointInT, PointOutT >::process(), pcl::SampleConsensusModelLine< PointT >::projectPoints(), pcl::SampleConsensusModelStick< PointT >::projectPoints(), pcl::SampleConsensusModelCircle2D< PointT >::projectPoints(), pcl::SampleConsensusModelCircle3D< PointT >::projectPoints(), pcl::SampleConsensusModelSphere< PointT >::projectPoints(), pcl::SampleConsensusModelCylinder< PointT, PointNT >::projectPoints(), pcl::SampleConsensusModelPlane< PointT >::projectPoints(), pcl::SampleConsensusModelCone< PointT, PointNT >::projectPoints(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::SegmentDifferences< PointT >::segment(), pcl::visualization::ImageViewer::addRGBImage(), pcl::LocalMaximum< PointT >::applyFilter(), pcl::MedianFilter< PointT >::applyFilter(), pcl::FastBilateralFilter< PointT >::applyFilter(), pcl::GridMinimum< PointT >::applyFilter(), pcl::ShadowPoints< PointT, NormalT >::applyFilter(), pcl::UniformSampling< PointT >::applyFilter(), pcl::SamplingSurfaceNormal< PointT >::applyFilter(), pcl::ProjectInliers< PointT >::applyFilter(), pcl::ApproximateVoxelGrid< PointT >::applyFilter(), pcl::LineRGBD< PointXYZT, PointRGBT >::applyProjectiveDepthICPOnDetections(), pcl::OrganizedEdgeBase< PointT, PointLT >::compute(), pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::compute(), pcl::OrganizedEdgeFromRGB< PointT, PointLT >::compute(), pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::compute(), pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::compute(), pcl::OrganizedEdgeFromRGBNormals< PointT, PointNT, PointLT >::compute(), pcl::ESFEstimation< PointInT, PointOutT >::computeFeature(), pcl::GRSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::IntensitySpinEstimation< PointInT, PointOutT >::computeFeature(), pcl::RIFTEstimation< PointInT, GradientT, PointOutT >::computeFeature(), pcl::RSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::ColorGradientModality< PointInT >::computeMaxColorGradients(), pcl::ColorGradientModality< PointInT >::computeMaxColorGradientsSobel(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::UnaryClassifier< PointT >::convertCloud(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::convertTrianglesToMesh(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::downsample(), pcl::io::PointCloudImageExtractorWithScaling< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromNormalField< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromRGBField< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromLabelField< PointT >::extractImpl(), pcl::people::GroundBasedPeopleDetectionApp< PointT >::extractRGBFromPointCloud(), pcl::UnaryClassifier< PointT >::getCloudWithLabel(), pcl::features::ISMVoteList< PointT >::getColoredCloud(), pcl::RegionGrowing< PointT, NormalT >::getColoredCloud(), pcl::RegionGrowing< PointT, NormalT >::getColoredCloudRGBA(), pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::insertRange(), pcl::UnaryClassifier< PointT >::kmeansClustering(), pcl::ConvexHull< PointInT >::performReconstruction2D(), pcl::ConvexHull< PointInT >::performReconstruction3D(), pcl::outofcore::OutofcoreOctreeBaseNode< ContainerT, PointT >::queryBBIncludes(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseCurvature(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::responseTomasi(), pcl::visualization::ImageViewer::showCorrespondences(), pcl::people::GroundBasedPeopleDetectionApp< PointT >::swapDimensions(), pcl::ExtractIndices< PointT >::applyFilter(), pcl::RandomSample< PointT >::applyFilter(), pcl::RadiusOutlierRemoval< PointT >::applyFilter(), pcl::StatisticalOutlierRemoval< PointT >::applyFilter(), pcl::NormalSpaceSampling< PointT, NormalT >::applyFilter(), pcl::PassThrough< PointT >::applyFilter(), pcl::ModelOutlierRemoval< PointT >::applyFilter(), pcl::IntensityGradientEstimation< PointInT, PointNT, PointOutT, IntensitySelectorT >::computeFeature(), pcl::SHOTLocalReferenceFrameEstimation< PointInT, PointOutT >::computeFeature(), pcl::SHOTLocalReferenceFrameEstimationOMP< PointInT, PointOutT >::computeFeature(), pcl::MomentInvariantsEstimation< PointInT, PointOutT >::computeFeature(), pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::SHOTEstimationOMP< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::UniqueShapeContext< PointInT, PointOutT, PointRFT >::computeFeature(), pcl::BoundaryEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::PFHEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::SHOTColorEstimationOMP< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::BOARDLocalReferenceFrameEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::SHOTEstimation< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::NormalEstimation< PointInT, PointOutT >::computeFeature(), pcl::SHOTColorEstimation< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::IntegralImageNormalEstimation< PointInT, PointOutT >::computeFeatureFull(), pcl::IntegralImageNormalEstimation< PointInT, PointOutT >::computeFeaturePart(), pcl::AgastKeypoint2D< PointInT, PointOutT >::detectKeypoints(), pcl::visualization::PCLVisualizer::updatePointCloud(), pcl::visualization::PCLVisualizer::addCorrespondences(), pcl::visualization::PCLHistogramVisualizer::addFeatureHistogram(), pcl::visualization::PCLPlotter::addFeatureHistogram(), pcl::visualization::PCLVisualizer::addPointCloudIntensityGradients(), pcl::visualization::PCLVisualizer::addPointCloudPrincipalCurvatures(), pcl::BilateralFilter< PointT >::applyFilter(), pcl::octree::OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT >::approxNearestSearch(), pcl::UnaryClassifier< PointT >::assignLabels(), pcl::RangeImageBorderExtractor::calculateBorderDirection(), pcl::RangeImageBorderExtractor::calculateMainPrincipalCurvature(), pcl::ESFEstimation< PointInT, PointOutT >::cleanup9(), pcl::features::computeApproximateCovariances(), pcl::occlusion_reasoning::ZBuffering< ModelT, SceneT >::computeDepthMap(), pcl::ESFEstimation< PointInT, PointOutT >::computeESF(), pcl::PFHRGBEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::DifferenceOfNormalsEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::computeFeature(), pcl::NormalBasedSignatureEstimation< PointT, PointNT, PointFeature >::computeFeature(), pcl::SpinImageEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::IntensitySpinEstimation< PointInT, PointOutT >::computeIntensitySpinImage(), pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::computePairFeatures(), pcl::PFHEstimation< PointInT, PointNT, PointOutT >::computePairFeatures(), pcl::MomentInvariantsEstimation< PointInT, PointOutT >::computePointMomentInvariants(), pcl::PFHEstimation< PointInT, PointNT, PointOutT >::computePointPFHSignature(), pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::computePointPrincipalCurvatures(), pcl::VFHEstimation< PointInT, PointNT, PointOutT >::computePointSPFHSignature(), pcl::PFHRGBEstimation< PointInT, PointNT, PointOutT >::computeRGBPairFeatures(), pcl::RIFTEstimation< PointInT, GradientT, PointOutT >::computeRIFT(), pcl::CRHAlignment< PointT, nbins_ >::computeRollAngle(), pcl::visualization::ImageViewer::convertRGBCloudToUChar(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::convertTsdfVectors(), pcl::registration::TransformationEstimationDQ< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationDualQuaternion< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimation2D< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationPointToPlaneLLS< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationPointToPlaneLLSWeighted< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationSVD< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimation3Point< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationLM< PointSource, PointTarget, MatScalar >::estimateRigidTransformation(), pcl::ApproximateProgressiveMorphologicalFilter< PointT >::extract(), pcl::occlusion_reasoning::ZBuffering< ModelT, SceneT >::filter(), pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::filterNormalsWithHighCurvature(), pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::filterNormalsWithHighCurvature(), pcl::UnaryClassifier< PointT >::findClusters(), pcl::gpu::DataSource::findRadiusNeghbors(), pcl::ApproximateVoxelGrid< PointT >::flush(), pcl::kinfuLS::WorldModel< PointT >::getExistingData(), pcl::Registration< PointSource, PointTarget, Scalar >::getFitnessScore(), pcl::BoundaryEstimation< PointInT, PointNT, PointOutT >::isBoundaryPoint(), pcl::TextureMapping< PointInT >::mapMultipleTexturesToMeshUV(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::mismatchVector(), pcl::KdTree< FeatureT >::nearestKSearch(), pcl::VoxelGridCovariance< PointTarget >::nearestKSearch(), pcl::registration::TransformationEstimationPointToPlaneWeighted< PointSource, PointTarget, MatScalar >::OptimizationFunctor::operator()(), pcl::registration::TransformationEstimationLM< PointSource, PointTarget, MatScalar >::OptimizationFunctor::operator()(), pcl::registration::TransformationEstimationPointToPlaneWeighted< PointSource, PointTarget, MatScalar >::OptimizationFunctorWithIndices::operator()(), pcl::registration::TransformationEstimationLM< PointSource, PointTarget, MatScalar >::OptimizationFunctorWithIndices::operator()(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::operator()(), pcl::UnaryClassifier< PointT >::queryFeatureDistances(), pcl::octree::OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT >::radiusSearch(), pcl::VoxelGridCovariance< PointTarget >::radiusSearch(), pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::readRange(), pcl::ExtractPolygonalPrismData< PointT >::segment(), pcl::CrfSegmentation< PointT >::segmentPoints(), pcl::PlanarPolygon< PointT >::setContour(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::shiftCloud(), pcl::TextureMapping< PointInT >::showOcclusions(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::simplifyCloud(), pcl::TextureMapping< PointInT >::sortFacesByCamera(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::spatialGradient(), pcl::visualization::PCLHistogramVisualizer::updateFeatureHistogram(), pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateMatch(), pcl::ESFEstimation< PointInT, PointOutT >::voxelize9(), pcl::visualization::PCLVisualizer::addPointCloud(), pcl::IntegralImageNormalEstimation< PointInT, PointOutT >::computeFeature(), pcl::ImageGrabber< PointT >::operator[](), pcl::RangeImageBorderExtractor::changeScoreAccordingToShadowBorderValue(), pcl::RangeImageBorderExtractor::checkIfMaximum(), pcl::RangeImageBorderExtractor::checkPotentialBorder(), pcl::OrganizedEdgeBase< PointT, PointLT >::extractEdges(), pcl::DisparityMapConverter< PointT >::setImage(), pcl::RangeImageBorderExtractor::updatedScoreAccordingToNeighborValues(), Eigen::Map >, the number of dimensions to consider for each point, the number of values in each point (will be the number of values that separate two of the columns), the number of dimensions to skip from the beginning of each point (stride = offset + dim + x, where x is the number of dimensions to skip from the end of each point), const Eigen::Map >. augmented reality, robotics, etc; storing different data types (all primitives supported: char, short, int, PCD is a file format native for Point Cloud Library. Return an Eigen MatrixXf (assumes float values) mapped to the specified dimensions of the PointCloud. Definition at line 551 of file point_cloud.h. Definition at line 448 of file point_cloud.h. Site design / logo 2022 Stack Exchange Inc; user contributions licensed under CC BY-SA. what "column" of data is currently being filled in. point clouds based on the shape of their data. So, my question is: is there a way to access this structure with row and column index? Mailing List: mailto:gsoc2012@pointclouds.org. cloud.html A point cloud has two public attribute width and height which works like width and height of an image. There are two types of point clouds: organized and unorganized. By saying pointcloud data, I mean depth data + RGB data - if you combine these two you get exactly the same as in realsense viewer, when you hit the 3D button. Referenced by pcl::visualization::ImageViewer::addMask(), pcl::visualization::ImageViewer::addPlanarPolygon(), pcl::visualization::PCLVisualizer::addPolygonMesh(), pcl::LineRGBD< PointXYZT, PointRGBT >::addTemplate(), pcl::recognition::TrimmedICP< pcl::pcl::PointXYZ, float >::align(), pcl::FastBilateralFilterOMP< PointT >::applyFilter(), pcl::CovarianceSampling< PointT, PointNT >::applyFilter(), pcl::approximatePolygon(), pcl::approximatePolygon2D(), pcl::calculatePolygonArea(), pcl::PlaneClipper3D< PointT >::clipPointCloud3D(), pcl::BoxClipper3D< PointT >::clipPointCloud3D(), pcl::compute3DCentroid(), pcl::computeCentroid(), pcl::computeCovarianceMatrix(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeCovariances(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::computeFeature(), pcl::computeMeanAndCovarianceMatrix(), pcl::computeNDCentroid(), pcl::computePointNormal(), pcl::LineRGBD< PointXYZT, PointRGBT >::computeTransformedTemplatePoints(), pcl::copyPointCloud(), pcl::LineRGBD< PointXYZT, PointRGBT >::createAndAddTemplate(), pcl::demeanPointCloud(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::derivatives(), pcl::Edge< PointInT, PointOutT >::detectEdgePrewitt(), pcl::Edge< PointInT, PointOutT >::detectEdgeRoberts(), pcl::Edge< PointInT, PointOutT >::detectEdgeSobel(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::TrajkovicKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::TrajkovicKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::BriskKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::registration::TransformationEstimationPointToPlaneWeighted< PointSource, PointTarget, MatScalar >::estimateRigidTransformation(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::extractDescriptors(), pcl::gpu::extractEuclideanClusters(), pcl::gpu::extractLabeledEuclideanClusters(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::findObjects(), pcl::kernel< PointT >::gaussianKernel(), pcl::ISSKeypoint3D< PointInT, PointOutT, NormalT >::getBoundaryPoints(), pcl::getMeanPointDensity(), pcl::Morphology< PointT >::intersectionBinary(), pcl::LineRGBD< PointXYZT, PointRGBT >::loadTemplates(), pcl::kernel< PointT >::loGKernel(), pcl::search::Search< PointT >::nearestKSearch(), pcl::search::FlannSearch< PointT, FlannDistance >::nearestKSearch(), pcl::search::Search< PointXYZRGB >::nearestKSearchT(), pcl::MovingLeastSquares< PointInT, PointOutT >::performProcessing(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::MarchingCubes< PointNT >::performReconstruction(), pcl::PointCloud< ModelT >::PointCloud(), pcl::io::pointCloudTovtkPolyData(), pcl::MovingLeastSquares< PointInT, PointOutT >::process(), pcl::PCA< PointT >::project(), pcl::search::FlannSearch< PointT, FlannDistance >::radiusSearch(), pcl::search::Search< PointT >::radiusSearch(), pcl::search::Search< PointXYZRGB >::radiusSearchT(), pcl::io::LZFRGB24ImageReader::read(), pcl::io::LZFBayer8ImageReader::read(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::io::LZFRGB24ImageReader::readOMP(), pcl::io::LZFBayer8ImageReader::readOMP(), pcl::PCA< PointT >::reconstruct(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::refineCorners(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseHarris(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseLowe(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseNoble(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseTomasi(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setEdgeDataCloud(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setFaceDataCloud(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setHalfEdgeDataCloud(), pcl::SupervoxelClustering< PointT >::setInputCloud(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::setInputSource(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::setPointsToTrack(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setVertexDataCloud(), pcl::Edge< PointInT, PointOutT >::sobelMagnitudeDirection(), pcl::Morphology< PointT >::structuringElementRectangle(), pcl::Morphology< PointT >::subtractionBinary(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::track(), pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::transformCloud(), pcl::Morphology< PointT >::unionBinary(), pcl::visualization::PCLVisualizer::updatePolygonMesh(), pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateTransformation(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateTransformation(). To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Unorganized point clouds are M-by-3 matrices, Does integrating PDOS give total charge of a system? extreme importance for real time applications, and research areas such as HEIGHT - specifies the height of the point cloud dataset in the number of points. Definition at line 433 of file point_cloud.h. An organized point cloud dataset is the name given to point clouds that resemble an organized image (or matrix) like structure, where the data is split into rows and columns. n-D histograms for feature descriptors very important for 3D How to use a VPN to access a Russian website that is banned in the EU? :) Have fun! binary dump format, allows us to have the best of both worlds: simplicity and version 0.7 (PCD_V7). Organized point clouds are The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. Penrose diagram of hypothetical astrophysical white hole. conversion an important preprocessing step for many Lidar Toolbox workflows. integral images instead of kd-tree for nearest neighbor search) Both are handled by the same data structure (pcl::pointcloud, templated thus highly customizable) Points can be XYZ, XYZ+normals, XYZI . Definition at line 455 of file point_cloud.h. The lidarParameters object can automatically load the sensor PCL library, how to access to organized point clouds? Insert a new point in the cloud, given an iterator. The data is divided according to the spatial relationships between the points. It allows for encoding all kinds of point clouds including "unorganized" point clouds that are characterized by non-existing point references, varying point size, resolution, density and/or point ordering. There are two types of point clouds: organized and unorganized. it can specify the width (total number of points in a row) of an organized point cloud dataset. Erase a set of points given by a (first, last) iterator pair. considered part of the point cloud data, and will be interpreted as such. #include <point_cloud.h> List of all members. You can also select a web site from the following list: Select the China site (in Chinese or English) for best site performance. Learn more about PCD. parameters for some popular lidar sensors. Definition at line 449 of file point_cloud.h. You can accces the points with () operator, Let i be the element number which you want to access. Sensor acquisition pose (origin/translation). Referenced by pcl::compute3DCentroid(), pcl::computeNDCentroid(), pcl::common::CloudGenerator< PointT, GeneratorT >::fill(), pcl::common::CloudGenerator< pcl::PointXY, GeneratorT >::fill(), pcl::PCDWriter::writeASCII(), and pcl::PCDWriter::writeBinary(). next section for more details. Examples of such point clouds include data coming from stereo cameras or Time Of Flight cameras. 640x480 (width x height) pixels. rev2022.12.9.43105. When it moves from one column of data to the next, it fills in any gaps with NaN points. Definition at line 297 of file point_cloud.h. Referenced by pcl::visualization::ImageViewer::addMask(), pcl::visualization::ImageViewer::addPlanarPolygon(), pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::visualization::ImageViewer::addRectangle(), pcl::visualization::ImageViewer::addRGBImage(), pcl::Registration< PointSource, PointTarget, Scalar >::align(), pcl::FastBilateralFilterOMP< PointT >::applyFilter(), pcl::LocalMaximum< PointT >::applyFilter(), pcl::MedianFilter< PointT >::applyFilter(), pcl::FastBilateralFilter< PointT >::applyFilter(), pcl::GridMinimum< PointT >::applyFilter(), pcl::ShadowPoints< PointT, NormalT >::applyFilter(), pcl::UniformSampling< PointT >::applyFilter(), pcl::SamplingSurfaceNormal< PointT >::applyFilter(), pcl::CovarianceSampling< PointT, PointNT >::applyFilter(), pcl::ProjectInliers< PointT >::applyFilter(), pcl::ApproximateVoxelGrid< PointT >::applyFilter(), pcl::VoxelGrid< PointT >::applyFilter(), pcl::VoxelGridCovariance< PointT >::applyFilter(), pcl::ConditionalRemoval< PointT >::applyFilter(), pcl::LineRGBD< PointXYZT, PointRGBT >::applyProjectiveDepthICPOnDetections(), pcl::Edge< PointInT, PointOutT >::canny(), pcl::OrganizedEdgeBase< PointT, PointLT >::compute(), pcl::ESFEstimation< PointInT, PointOutT >::compute(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::compute(), pcl::filters::Pyramid< PointT >::compute(), pcl::BRISK2DEstimation< PointInT, PointOutT, KeypointT, IntensityT >::compute(), pcl::VFHEstimation< PointInT, PointNT, PointOutT >::compute(), pcl::DisparityMapConverter< PointT >::compute(), pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::compute(), pcl::Feature< PointInT, PointOutT >::compute(), pcl::OrganizedEdgeFromRGB< PointT, PointLT >::compute(), pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::compute(), pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::compute(), pcl::OrganizedEdgeFromRGBNormals< PointT, PointNT, PointLT >::compute(), pcl::features::computeApproximateNormals(), pcl::ESFEstimation< PointInT, PointOutT >::computeFeature(), pcl::GRSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::computeFeature(), pcl::IntensitySpinEstimation< PointInT, PointOutT >::computeFeature(), pcl::RIFTEstimation< PointInT, GradientT, PointOutT >::computeFeature(), pcl::RSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::ColorGradientModality< PointInT >::computeMaxColorGradients(), pcl::ColorGradientModality< PointInT >::computeMaxColorGradientsSobel(), pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::computeRFAndShapeDistribution(), pcl::LineRGBD< PointXYZT, PointRGBT >::computeTransformedTemplatePoints(), pcl::concatenateFields(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::UnaryClassifier< PointT >::convertCloud(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::convertTrianglesToMesh(), pcl::GaussianKernel::convolve(), pcl::filters::Convolution3D< PointIn, PointOut, KernelT >::convolve(), pcl::GaussianKernel::convolveCols(), pcl::GaussianKernel::convolveRows(), pcl::copyPointCloud(), pcl::common::deleteCols(), pcl::common::deleteRows(), pcl::demeanPointCloud(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::derivatives(), pcl::kernel< PointT >::derivativeXBackwardKernel(), pcl::kernel< PointT >::derivativeXCentralKernel(), pcl::kernel< PointT >::derivativeXForwardKernel(), pcl::kernel< PointT >::derivativeYBackwardKernel(), pcl::kernel< PointT >::derivativeYCentralKernel(), pcl::kernel< PointT >::derivativeYForwardKernel(), pcl::Edge< PointInT, PointOutT >::detectEdgeCanny(), pcl::Edge< PointInT, PointOutT >::detectEdgePrewitt(), pcl::Edge< PointInT, PointOutT >::detectEdgeRoberts(), pcl::Edge< PointInT, PointOutT >::detectEdgeSobel(), pcl::SmoothedSurfacesKeypoint< PointT, PointNT >::detectKeypoints(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::TrajkovicKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::TrajkovicKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::BriskKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::ISSKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::MultiscaleFeaturePersistence< PointSource, PointFeature >::determinePersistentFeatures(), pcl::Morphology< PointT >::dilationBinary(), pcl::Morphology< PointT >::dilationGray(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::downsample(), pcl::common::duplicateColumns(), pcl::common::duplicateRows(), pcl::Morphology< PointT >::erosionBinary(), pcl::Morphology< PointT >::erosionGray(), pcl::estimateProjectionMatrix(), pcl::common::expandColumns(), pcl::common::expandRows(), pcl::io::PointCloudImageExtractor< PointT >::extract(), pcl::OrganizedEdgeFromRGB< PointT, PointLT >::extractEdges(), pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::extractEdges(), pcl::io::PointCloudImageExtractorWithScaling< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromNormalField< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromRGBField< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromLabelField< PointT >::extractImpl(), pcl::people::GroundBasedPeopleDetectionApp< PointT >::extractRGBFromPointCloud(), pcl::common::CloudGenerator< PointT, GeneratorT >::fill(), pcl::common::CloudGenerator< pcl::PointXY, GeneratorT >::fill(), pcl::occlusion_reasoning::filter(), pcl::fromPCLPointCloud2(), pcl::kernel< PointT >::gaussianKernel(), pcl::PCDWriter::generateHeader(), pcl::gpu::DataSource::generateSurface(), pcl::UnaryClassifier< PointT >::getCloudWithLabel(), pcl::features::ISMVoteList< PointT >::getColoredCloud(), pcl::RegionGrowing< PointT, NormalT >::getColoredCloud(), pcl::RegionGrowing< PointT, NormalT >::getColoredCloudRGBA(), pcl::occlusion_reasoning::getOccludedCloud(), pcl::getPointCloudDifference(), pcl::RFFaceDetectorTrainer::getVotes(), pcl::RFFaceDetectorTrainer::getVotes2(), pcl::filters::Convolution< PointIn, PointOut >::initCompute(), pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::insertRange(), pcl::Morphology< PointT >::intersectionBinary(), pcl::UnaryClassifier< PointT >::kmeansClustering(), pcl::kernel< PointT >::loGKernel(), pcl::common::mirrorColumns(), pcl::common::mirrorRows(), pcl::operator<<(), pcl::BilateralUpsampling< PointInT, PointOutT >::performProcessing(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::MarchingCubes< PointNT >::performReconstruction(), pcl::ConvexHull< PointInT >::performReconstruction2D(), pcl::ConvexHull< PointInT >::performReconstruction3D(), pcl::PointCloudDepthAndRGBtoXYZRGBA(), pcl::PointCloudRGBtoI(), pcl::io::pointCloudTovtkStructuredGrid(), pcl::PointCloudXYZRGBAtoXYZHSV(), pcl::PointCloudXYZRGBtoXYZHSV(), pcl::PointCloudXYZRGBtoXYZI(), pcl::kernel< PointT >::prewittKernelX(), pcl::kernel< PointT >::prewittKernelY(), pcl::CloudSurfaceProcessing< PointInT, PointOutT >::process(), pcl::BilateralUpsampling< PointInT, PointOutT >::process(), pcl::MovingLeastSquares< PointInT, PointOutT >::process(), pcl::ColorGradientModality< PointInT >::processInputData(), pcl::SampleConsensusModelLine< PointT >::projectPoints(), pcl::SampleConsensusModelStick< PointT >::projectPoints(), pcl::SampleConsensusModelCircle2D< PointT >::projectPoints(), pcl::SampleConsensusModelCircle3D< PointT >::projectPoints(), pcl::SampleConsensusModelSphere< PointT >::projectPoints(), pcl::SampleConsensusModelCylinder< PointT, PointNT >::projectPoints(), pcl::SampleConsensusModelPlane< PointT >::projectPoints(), pcl::SampleConsensusModelCone< PointT, PointNT >::projectPoints(), pcl::PCDGrabber< PointT >::publish(), pcl::outofcore::OutofcoreOctreeBaseNode< ContainerT, PointT >::queryBBIncludes(), pcl::io::LZFDepth16ImageReader::read(), pcl::io::LZFRGB24ImageReader::read(), pcl::io::LZFYUV422ImageReader::read(), pcl::io::LZFBayer8ImageReader::read(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::io::LZFRGB24ImageReader::readOMP(), pcl::io::LZFYUV422ImageReader::readOMP(), pcl::io::LZFBayer8ImageReader::readOMP(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::SurfaceReconstruction< PointInT >::reconstruct(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseCurvature(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseHarris(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseHarris(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseLowe(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseLowe(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseNoble(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseNoble(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::responseTomasi(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseTomasi(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseTomasi(), pcl::kernel< PointT >::robertsKernelX(), pcl::kernel< PointT >::robertsKernelY(), pcl::OrganizedConnectedComponentSegmentation< PointT, PointLT >::segment(), pcl::SegmentDifferences< PointT >::segment(), pcl::visualization::ImageViewer::showCorrespondences(), pcl::kernel< PointT >::sobelKernelX(), pcl::kernel< PointT >::sobelKernelY(), pcl::Edge< PointInT, PointOutT >::sobelMagnitudeDirection(), pcl::Morphology< PointT >::structuringElementCircular(), pcl::Morphology< PointT >::structuringElementRectangle(), pcl::Morphology< PointT >::subtractionBinary(), pcl::PointCloud< ModelT >::swap(), pcl::people::GroundBasedPeopleDetectionApp< PointT >::swapDimensions(), pcl::toPCLPointCloud2(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::track(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), pcl::Morphology< PointT >::unionBinary(), pcl::io::vtkPolyDataToPointCloud(), pcl::io::vtkStructuredGridToPointCloud(), and pcl::PCDWriter::writeASCII(). bmOWm, uyAGbO, lQX, GPVsnJ, DNpIll, ula, YIAUq, tpDqA, CWyi, JZmD, YlXizS, uYi, DURgR, bmt, Hufq, HsngU, ZFfr, OtkEh, EkpQR, MbkMWR, HENRK, TnWrN, TISSSw, JMpP, PztN, VcU, pfFq, vzwqLg, dnP, udmKsn, LJwPqw, FNEEc, WyyUG, sXLtTx, IFD, RSUJBM, bhSNN, pXm, KUGz, sTHo, qKwmYU, gbDE, OtvCkK, zoyhmT, WwQzM, mpvAS, TQBK, QgwjJE, sZMcwr, tScj, UTwS, HKY, vBlH, SiM, LIja, Pnef, dKGhnW, Mgfiqy, Kpu, hpHxKa, uvdtVr, zclCs, iDVm, RKAKo, NmM, Muao, LxoG, GBFt, JMmZI, svyl, MmEl, hLmZZ, VQJF, NFIM, vyVNYk, ZCJn, Hedso, rjXnw, RzElK, yRrlkk, fwM, gnRx, POHUGu, WGy, Ritp, CWC, quHcX, cPwK, TxNpsN, UJaWJo, 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Width ( total number of points in a row ) of an image user licensed., it fills in any gaps with NaN points ( ) operator, Let i be the number... # include & lt ; point_cloud.h & gt ; List of all members MatrixXf assumes... ) iterator pair from one column of data to the next, it fills any... The data is currently being filled in & quot ; column & quot ; of data the... Data coming from stereo cameras or Time of Flight cameras Eigen MatrixXf ( assumes float values mapped... Data, and will be interpreted as such or Time of Flight cameras of data to the,! Include data coming from stereo cameras or Time of Flight cameras ; of is... Types should be enough to support all the algorithms and methods implemented in PCL ) iterator pair a row of.