Point Cloud Library (PCL)
1.9.1dev

►Nboost  
►Ndetail  
Cis_random_access< eigen_listS >  
Cis_random_access< eigen_vecS >  
Ccontainer_gen< eigen_listS, ValueType >  
Ccontainer_gen< eigen_vecS, ValueType >  
Ceigen_listS  
Ceigen_vecS  
Cparallel_edge_traits< eigen_listS >  
Cparallel_edge_traits< eigen_vecS >  
►NEigen  
CNumTraits< pcl::ndt2d::NormalDist< PointT > >  
CPolynomialSolver< _Scalar, 2 >  
►Nflann  
CIndex  
CL2  
CL2_Simple  
CMatrix  
CNNIndex  
►NLoki  
►NTL  
CTypeAt  
CTypeAt< Typelist< Head, Tail >, 0 >  
CTypeAt< Typelist< Head, Tail >, i >  
CInt2Type  
CNullType  
CTypelist  
►NNcvCTprep  Compiletime assert namespace 
CassertTest  
CCT_ASSERT_FAILURE  
CCT_ASSERT_FAILURE< true >  
►NNCVRuntimeTemplateBool  
CKernelCaller  
CKernelCaller< TList, 0, Func >  
►Nopenni_wrapper  
CDepthImage  This class provides methods to fill a depth or disparity image 
CDeviceKinect  Concrete implementation of the interface OpenNIDevice for a MS Kinect device 
CDeviceONI  Concrete implementation of the interface OpenNIDevice for a virtual device playing back an ONI file 
CDevicePrimesense  Concrete implementation of the interface OpenNIDevice for a Primesense device 
CDeviceXtionPro  Concrete implementation of the interface OpenNIDevice for a Asus Xtion Pro device 
CImage  Image class containing just a reference to image meta data 
CImageBayerGRBG  This class provides methods to fill a RGB or Grayscale image buffer from underlying Bayer pattern image 
CImageRGB24  This class provides methods to fill a RGB or Grayscale image buffer from underlying RGB24 image 
CImageYUV422  Concrete implementation of the interface Image for a YUV 422 image used by Primesense devices 
CIRImage  Class containing just a reference to IR meta data 
►COpenNIDevice  Class representing an astract device for OpenNI devices: Primesense PSDK, Microsoft Kinect, Asus Xtion Pro/Live 
CShiftConversion  
►COpenNIDriver  Driver class implemented as Singleton 
CDeviceContext  
COpenNIException  General exception class 
CShiftToDepthConverter  This class provides conversion of the openni 11bit shift data to depth; 
►Npcl  This file defines compatibility wrappers for low level I/O functions 
►Ncommon  
CCloudGenerator  
CCloudGenerator< pcl::PointXY, GeneratorT >  
CIntensityFieldAccessor  
CIntensityFieldAccessor< pcl::InterestPoint >  
CIntensityFieldAccessor< pcl::PointNormal >  
CIntensityFieldAccessor< pcl::PointSurfel >  
CIntensityFieldAccessor< pcl::PointWithRange >  
CIntensityFieldAccessor< pcl::PointWithScale >  
CIntensityFieldAccessor< pcl::PointWithViewpoint >  
CIntensityFieldAccessor< pcl::PointXYZ >  
CIntensityFieldAccessor< pcl::PointXYZHSV >  
CIntensityFieldAccessor< pcl::PointXYZL >  
CIntensityFieldAccessor< pcl::PointXYZLNormal >  
CIntensityFieldAccessor< pcl::PointXYZRGB >  
CIntensityFieldAccessor< pcl::PointXYZRGBA >  
CIntensityFieldAccessor< pcl::PointXYZRGBL >  
CIntensityFieldAccessor< pcl::PointXYZRGBNormal >  
Cnormal_distribution  Normal distribution 
►CNormalGenerator  NormalGenerator class generates a random number from a normal distribution specified by (mean, sigma) 
CParameters  
Cuniform_distribution  Uniform distribution dummy struct 
Cuniform_distribution< T, std::enable_if_t< std::is_floating_point< T >::value > >  Uniform distribution float specialized 
Cuniform_distribution< T, std::enable_if_t< std::is_integral< T >::value > >  Uniform distribution int specialized 
►CUniformGenerator  UniformGenerator class generates a random number from range [min, max] at each run picked according to a uniform distribution i.e eaach number within [min, max] has almost the same probability of being drawn 
CParameters  
►Nconsole  
CTicToc  
►Ncuda  
►Ndetail  
CDjSets  
CGraph  
CGraphEdge  
CSegmLink  
CSegmLinkVal  
CAddCovariances  Adds two matrices elementwise 
CAddPoints  Simple kernel to add two points 
CChangeColor  
CCheckPlanarInlier  Check if a certain tuple is a point inlier 
CCheckPlanarInlierIndices  Check if a certain tuple is a point inlier 
CCheckPlanarInlierKinectIndices  Check if a certain tuple is a point inlier 
CCheckPlanarInlierKinectNormalIndices  Check if a certain tuple is a point inlier 
CCheckPlanarInlierNormalIndices  Check if a certain tuple is a point inlier 
CComputeCovarianceForPoint  Kernel to compute a ``covariance matrix'' for a single point 
CComputeXYZ  Compute the XYZ values for a point based on disparity information 
CComputeXYZRGB  Compute the XYZ and RGB values for a point based on disparity information 
Cconvert_point_to_float3  Simple kernel to convert a PointXYZRGB to float3 
CCountPlanarInlier  Check if a certain tuple is a point inlier 
CCovarianceMatrix  Misnamed class holding a 3x3 matrix 
CCreate1PointPlaneHypothesis  Check if a certain tuple is a point inlier 
CCreate1PointPlaneSampleHypothesis  Check if a certain tuple is a point inlier 
CCreatePlaneHypothesis  Check if a certain tuple is a point inlier 
CDebayerBilinear  
CDebayering  
CDebayeringDownsampling  
CDeleteIndices  Check if a certain tuple is a point inlier 
CDevice  Device helper class 
CDisparityBoundSmoothing  
CDisparityClampedSmoothing  
CDisparityHelperMap  
CDisparityToCloud  Disparity to PointCloudAOS generator 
CdownsampleIndices  
CFastNormalEstimationKernel  
CHost  Host helper class 
CisInlier  Check if a certain tuple is a point inlier 
CisNaNPoint  
CisNotInlier  
CisNotZero  
CMultiRandomSampleConsensus  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 
CNewCheckPlanarInlier  Check if a certain tuple is a point inlier 
CNormalDeviationKernel  
CNormalEstimationKernel  
COpenNIRGB  Simple structure holding RGB data 
COrganizedRadiusSearch  Kernel to compute a radius neighborhood given a organized point cloud (aka range image cloud) 
Cparallel_random_generator  
CPCLCUDABase  PCL base class 
CPointCloudAOS  PointCloudAOS represents an AOS (Array of Structs) PointCloud implementation for CUDA processing 
CPointCloudSOA  PointCloudSOA represents a SOA (Struct of Arrays) PointCloud implementation for CUDA processing 
CPointIterator  
CPointIterator< Device, T >  
CPointIterator< Host, T >  
CPointXYZRGB  Default point xyzrgb structure 
CRandomSampleConsensus  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 
CRGB  Default RGB structure, defined as a union over 4 chars 
CSampleConsensus  
CSampleConsensusModel  SampleConsensusModel represents the base model class 
CSampleConsensusModel1PointPlane  SampleConsensusModel1PointPlane defines a model for 3D plane segmentation 
CSampleConsensusModelPlane  SampleConsensusModelPlane defines a model for 3D plane segmentation 
CScopeTimeCPU  Class to measure the time spent in a scope 
CScopeTimeGPU  Class to measure the time spent in a scope 
CSetColor  
CStorageAllocator  
CStorageAllocator< Device, T >  
CStorageAllocator< Host, T >  
CStoragePointer  
CStoragePointer< Device, T >  
CStoragePointer< Host, T >  
CYUV2RGB  
CYUV2RGBKernel  
►Ndeprecated  
CT  
►Ndetail  
CAccumulatorCurvature  
CAccumulatorIntensity  
CAccumulatorLabel  
CAccumulatorNormal  
CAccumulatorRGBA  
CAccumulators  
CAccumulatorXYZ  
CAddPoint  
CCopyPointHelper  
CCopyPointHelper< PointInT, PointOutT, typename boost::enable_if< boost::is_same< PointInT, PointOutT > >::type >  
CCopyPointHelper< PointInT, PointOutT, typename boost::enable_if< boost::mpl::and_< boost::mpl::not_< boost::is_same< PointInT, PointOutT > >, boost::mpl::or_< boost::mpl::and_< pcl::traits::has_field< PointInT, pcl::fields::rgb >, pcl::traits::has_field< PointOutT, pcl::fields::rgba > >, boost::mpl::and_< pcl::traits::has_field< PointInT, pcl::fields::rgba >, pcl::traits::has_field< PointOutT, pcl::fields::rgb > > > > >::type >  
CCopyPointHelper< PointInT, PointOutT, typename boost::enable_if< boost::mpl::and_< boost::mpl::not_< boost::is_same< PointInT, PointOutT > >, boost::mpl::or_< boost::mpl::not_< pcl::traits::has_color< PointInT > >, boost::mpl::not_< pcl::traits::has_color< PointOutT > >, boost::mpl::and_< pcl::traits::has_field< PointInT, pcl::fields::rgb >, pcl::traits::has_field< PointOutT, pcl::fields::rgb > >, boost::mpl::and_< pcl::traits::has_field< PointInT, pcl::fields::rgba >, pcl::traits::has_field< PointOutT, pcl::fields::rgba > > > > >::type >  
CFieldAdder  
CFieldMapper  
CFieldMapping  
CGetPoint  
►CIsAccumulatorCompatible  
Capply  
CTransformer  A helper struct to apply an SO3 or SE3 transform to a 3D point 
►Ndevice  
►NkinfuLS  
CBlock  
►CEigen33  
CMiniMat  
CEmulation  
Cfloat12  
Cfloat8  
CIntr  Camera intrinsics structure 
CLightSource  Light source collection 
CMat33  3x3 Matrix for device code 
Cnumeric_limits  
Cnumeric_limits< float >  
Cnumeric_limits< short >  
CWarp  
Cbit_not  
CBlock  
CCalcMorton  
CCompareByLevelCode  
CConnectedComponents  
CCUDATree  Struct that holds a single RDF tree in GPU 
CDilatation  
►CEigen33  
CMiniMat  
CEmulation  
CFacetStream  
Cfloat12  
Cfloat8  
CHistogram  
CInitalSimplex  
CIntr  Camera intrinsics structure 
CLessThanByFacet  
CLightSource  Light source collection 
CMat33  3x3 Matrix for device code 
CMorton  
CMultiTreeLiveProc  Processor using multiple trees 
CNonCachedLoad  
Cnumeric_limits  
Cnumeric_limits< bool >  
Cnumeric_limits< char >  
Cnumeric_limits< double >  
Cnumeric_limits< float >  
Cnumeric_limits< int >  
Cnumeric_limits< long >  
Cnumeric_limits< short >  
Cnumeric_limits< signed char >  
Cnumeric_limits< unsigned char >  
Cnumeric_limits< unsigned int >  
Cnumeric_limits< unsigned long >  
Cnumeric_limits< unsigned short >  
COctreeGlobal  
COctreeGlobalWithBox  
►COctreeImpl  
COctreeDataHost  
COctreeIteratorDevice  
COctreeIteratorDeviceNS  
COctreePriorityIteratorDevice  
CplusWeighted  
CPointStream  
CPPFRGBSignature  
CPPFSignature  
CPrincipalCurvatures  
Cprob_histogram  
CProbabilityProc  Implementation Class to process probability histograms on GPU 
CStatic  
CStatic< true >  
CVFHEstimationImpl  
CWarp  
►Nexperimental  
CEuclideanClusterComparator  
►Nface_detection  
CFaceDetectorDataProvider  
CFeatureHandlerDepthAverage  
CFeatureType  
CPoseClassRegressionVarianceStatsEstimator  Statistics estimator for regression trees which optimizes information gain and pose parameters error 
CRFTreeNode  
CTrainingExample  
►Nfeatures  
CISMModel  The assignment of this structure is to store the statistical/learned weights and other information of the trained Implict Shape Model algorithm 
CISMVoteList  This class is used for storing, analyzing and manipulating votes obtained from ISM algorithm 
►Nfilters  
CConvolution  Convolution is a mathematical operation on two functions f and g, producing a third function that is typically viewed as a modified version of one of the original functions 
CConvolution3D  Convolution3D handles the non organized case where width and height are unknown or if you are only interested in convolving based on local neighborhood information 
CConvolvingKernel  Class ConvolvingKernel base class for all convolving kernels 
CConvolvingKernel< PointT, pcl::Normal >  
CConvolvingKernel< PointT, pcl::PointXY >  
CGaussianKernel  Gaussian kernel implementation interface Use this as implementation reference 
CGaussianKernelRGB  Gaussian kernel implementation interface with RGB channel handling Use this as implementation reference 
CPyramid  Pyramid constructs a multiscale representation of an organised point cloud 
►Ngeometry  
CDefaultMeshTraits  The mesh traits are used to set up compile time settings for the mesh 
CEdgeIndex  Index used to access elements in the halfedge mesh 
CFace  A face is a closed loop of edges 
CFaceAroundFaceCirculator  Circulates clockwise around a face and returns an index to the face of the outer halfedge (the target) 
CFaceAroundVertexCirculator  Circulates counterclockwise around a vertex and returns an index to the face of the outgoing halfedge (the target) 
CFaceIndex  Index used to access elements in the halfedge mesh 
CHalfEdge  An edge is a connection between two vertices 
CHalfEdgeIndex  Index used to access elements in the halfedge mesh 
CIncomingHalfEdgeAroundVertexCirculator  Circulates counterclockwise around a vertex and returns an index to the incoming halfedge (the target) 
CInnerHalfEdgeAroundFaceCirculator  Circulates clockwise around a face and returns an index to the inner halfedge (the target) 
CMeshBase  Base class for the halfedge mesh 
CMeshIO  Read / write the halfedge mesh from / to a file 
CNoData  No data is associated with the vertices / halfedges / edges / faces 
COuterHalfEdgeAroundFaceCirculator  Circulates clockwise around a face and returns an index to the outer halfedge (the target) 
COutgoingHalfEdgeAroundVertexCirculator  Circulates counterclockwise around a vertex and returns an index to the outgoing halfedge (the target) 
CPolygonMesh  General halfedge mesh that can store any polygon with a minimum number of vertices of 3 
CPolygonMeshTag  Tag describing the type of the mesh 
CQuadMesh  Halfedge mesh that can only store quads 
CQuadMeshTag  Tag describing the type of the mesh 
CTriangleMesh  Halfedge mesh that can only store triangles 
CTriangleMeshTag  Tag describing the type of the mesh 
CVertex  A vertex is a node in the mesh 
CVertexAroundFaceCirculator  Circulates clockwise around a face and returns an index to the terminating vertex of the inner halfedge (the target) 
CVertexAroundVertexCirculator  Circulates counterclockwise around a vertex and returns an index to the terminating vertex of the outgoing halfedge (the target) 
CVertexIndex  Index used to access elements in the halfedge mesh 
►Ngpu  
►NkinfuLS  
CCaptureOpenNI  
CColorVolume  ColorVolume class 
CCyclicalBuffer  CyclicalBuffer implements a cyclical TSDF buffer 
CKinfuTracker  KinfuTracker class encapsulates implementation of Microsoft Kinect Fusion algorithm 
CMarchingCubes  MarchingCubes implements MarchingCubes functionality for TSDF volume on GPU 
CPixelRGB  Input/output pixel format for KinfuTracker 
CRayCaster  Class that performs raycasting for TSDF volume 
CStandaloneMarchingCubes  The Standalone Marching Cubes Class provides encapsulated functionality for the Marching Cubes implementation originally by Anatoly Baksheev 
Ctsdf_buffer  Structure to handle buffer addresses 
►CTsdfVolume  TsdfVolume class 
CHeader  Structure storing voxel grid resolution, volume size (in mm) and element_size of data stored on host 
►Npeople  
►Ntrees  
CAttribLocation  
CHistogram  
CHistogramPair  
CLabeledAttrib  
CLabeledFeature  
CNode  
CSplitPoint  
CBlob2  This structure contains all parameters to describe blobs and their parent/child relations 
CFaceDetector  
COrganizedPlaneDetector  
CPeopleDetector  
CPersonAttribs  
CProbabilityProcessor  
CRDFBodyPartsDetector  
CTree2  This structure contains all parameters to describe the segmented tree 
CAsyncCopy  
CCaptureOpenNI  
CColorVolume  ColorVolume class 
►CDataSource  
CNormal2PointXYZ  
CDeviceArray  DeviceArray class 
CDeviceArray2D  DeviceArray2D class 
CDeviceMemory  DeviceMemory class 
CDeviceMemory2D  DeviceMemory2D class 
CDevPtr  
CEuclideanClusterExtraction  EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense, depending on pcl::gpu::octree 
CEuclideanLabeledClusterExtraction  EuclideanLabeledClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense, depending on pcl::gpu::octree 
CFeature  Feature represents the base feature class 
CFeatureFromNormals  Feature represents the base feature class that takes normals as input also 
CFPFHEstimation  Class for FPFH estimation 
CKinfuTracker  KinfuTracker class encapsulates implementation of Microsoft Kinect Fusion algorithm 
CMarchingCubes  MarchingCubes implements MarchingCubes functionality for TSDF volume on GPU 
CNeighborIndices  
CNormalEstimation  Class for normal estimation 
COctree  Octree implementation on GPU 
CParticleFilterGPUTracker  
CPFHEstimation  Class for PFH estimation 
CPFHRGBEstimation  Class for PFHRGB estimation 
CPixelRGB  Input/output pixel format for KinfuTracker 
CPPFEstimation  ** 
CPPFRGBEstimation  ** 
CPPFRGBRegionEstimation  ** 
CPrincipalCurvaturesEstimation  Class for PPFRGBRegion estimation 
CPseudoConvexHull3D  
CPtrStep  
CPtrStepSz  
CPtrSz  
CRayCaster  Class that performs raycasting for TSDF volume 
CScopeTimer  
CSeededHueSegmentation  
CSpinImageEstimation  Class for SpinImages estimation 
CTextureBinder  
CTimer  
CTsdfVolume  TsdfVolume class 
CVFHEstimation  ** 
►Nio  
►Ndepth_sense  
CDepthSenseDeviceManager  A helper class for enumerating and managing access to DepthSense devices 
CDepthSenseGrabberImpl  
►Nopenni2  
COpenNI2Device  
COpenNI2DeviceInfo  
COpenNI2DeviceManager  
COpenNI2FrameListener  
COpenNI2TimerFilter  
COpenNI2VideoMode  
►Nply  
►Cply_parser  Class ply_parser parses a PLY file and generates appropriate atomic parsers for the body 
Clist_property_begin_callback_type  
Clist_property_definition_callback_type  
Clist_property_definition_callbacks_type  
Clist_property_element_callback_type  
Clist_property_end_callback_type  
Cscalar_property_callback_type  
Cscalar_property_definition_callback_type  
Cscalar_property_definition_callbacks_type  
Ctype_traits  
►Nreal_sense  
CRealSenseDevice  
CRealSenseDeviceManager  
CAverageBuffer  A buffer that computes running window average of the data inserted 
CBuffer  An abstract base class for fixedsize data buffers 
CCameraParameters  Basic camera parameters placeholder 
CCompressionPointTraits  
CCompressionPointTraits< PointXYZRGB >  
CCompressionPointTraits< PointXYZRGBA >  
CconfigurationProfile_t  
CDeBayer  Various debayering methods 
CDepthImage  This class provides methods to fill a depth or disparity image 
CFrameWrapper  Pure abstract interface to wrap native frame data types 
CImage  Image interface class providing an interface to fill a RGB or Grayscale image buffer 
CImageRGB24  This class provides methods to fill a RGB or Grayscale image buffer from underlying RGB24 image 
CImageYUV422  Concrete implementation of the interface Image for a YUV 422 image used by Primesense devices 
CIOException  General IO exception class 
CIRImage  Class containing just a reference to IR meta data 
CLZFBayer8ImageReader  PCLLZF 8bit Bayer image format reader 
CLZFBayer8ImageWriter  PCLLZF 8bit Bayer image format writer 
CLZFDepth16ImageReader  PCLLZF 16bit depth image format reader 
CLZFDepth16ImageWriter  PCLLZF 16bit depth image format writer 
CLZFImageReader  PCLLZF image format reader 
CLZFImageWriter  PCLLZF image format writer 
CLZFRGB24ImageReader  PCLLZF 24bit RGB image format reader 
CLZFRGB24ImageWriter  PCLLZF 24bit RGB image format writer 
CLZFYUV422ImageReader  PCLLZF 8bit Bayer image format reader 
CLZFYUV422ImageWriter  PCLLZF 16bit YUV422 image format writer 
CMedianBuffer  A buffer that computes running window median of the data inserted 
COctreePointCloudCompression  Octree pointcloud compression class 
COrganizedConversion  
COrganizedConversion< PointT, false >  
COrganizedConversion< PointT, true >  
COrganizedPointCloudCompression  
CPointCloudImageExtractor  Base Image Extractor class for organized point clouds 
CPointCloudImageExtractorFromCurvatureField  Image Extractor which uses the data present in the "curvature" field to produce a curvature map (as a monochrome image with mono16 encoding) 
CPointCloudImageExtractorFromIntensityField  Image Extractor which uses the data present in the "intensity" field to produce a monochrome intensity image (with mono16 encoding) 
CPointCloudImageExtractorFromLabelField  Image Extractor which uses the data present in the "label" field to produce either monochrome or RGB image where different labels correspond to different colors 
CPointCloudImageExtractorFromNormalField  Image Extractor which uses the data present in the "normal" field 
CPointCloudImageExtractorFromRGBField  Image Extractor which uses the data present in the "rgb" or "rgba" fields to produce a color image with rgb8 encoding 
CPointCloudImageExtractorFromZField  Image Extractor which uses the data present in the "z" field to produce a depth map (as a monochrome image with mono16 encoding) 
CPointCloudImageExtractorWithScaling  Image Extractor extension which provides functionality to apply scaling to the values extracted from a field 
CSingleBuffer  A simple buffer that only stores data 
CTARHeader  A TAR file's header, as described on http://en.wikipedia.org/wiki/Tar_%28file_format%29 
►Nism  
►CImplicitShapeModelEstimation  This class implements Implicit Shape Model algorithm described in "Hough Transforms and 3D SURF for robust three dimensional classication" by Jan Knopp1, Mukta Prasad, Geert Willems1, Radu Timofte, and Luc Van Gool 
CLocationInfo  This structure stores the information about the keypoint 
CTC  This structure is used for determining the end of the kmeans clustering process 
CVisualWordStat  Structure for storing the visual word 
►Nkeypoints  
►Nagast  
►CAbstractAgastDetector  Abstract detector class for AGAST corner point detectors 
CCompareScoreIndex  Score index comparator 
CScoreIndex  Structure holding an index and the associated keypoint score 
CAgastDetector5_8  Detector class for AGAST corner point detector (5_8) 
CAgastDetector7_12s  Detector class for AGAST corner point detector (7_12s) 
COastDetector9_16  Detector class for AGAST corner point detector (OAST 9_16) 
►Nbrisk  
►CLayer  A layer in the BRISK detector pyramid 
CCommonParams  
CScaleSpace  BRISK Scale Space helper 
►Ninternal  
CAgastApplyNonMaxSuppresion  
CAgastApplyNonMaxSuppresion< pcl::PointUV >  
CAgastDetector  
CAgastDetector< pcl::PointUV >  
►NkinfuLS  
CScreenshotManager  Screenshot Manager saves a screenshot with the corresponding camera pose from Kinfu 
CWorldModel  WorldModel maintains a 3D point cloud that can be queried and updated via helper functions 
►Nndt2d  
CNDT2D  Build a Normal Distributions Transform of a 2D point cloud 
CNDTSingleGrid  Build a set of normal distributions modelling a 2D point cloud, and provide the value and derivatives of the model at any point via the test (...) function 
CNormalDist  A normal distribution estimation class 
CValueAndDerivatives  Class to store vector value and first and second derivatives (grad vector and hessian matrix), so they can be returned easily from functions 
►Nocclusion_reasoning  
CZBuffering  Class to reason about occlusions 
►Noctree  
CBufferedBranchNode  
CColorCoding  ColorCoding class 
CIteratorState  
COctree2BufBase  Octree double buffer class 
COctreeBase  Octree class 
COctreeBranchNode  Abstract octree branch class 
COctreeBreadthFirstIterator  Octree iterator class 
COctreeContainerBase  Octree container class that can serve as a base to construct own leaf node container classes 
COctreeContainerEmpty  Octree container class that does not store any information 
COctreeContainerPointIndex  Octree container class that does store a single point index 
COctreeContainerPointIndices  Octree container class that does store a vector of point indices 
COctreeDepthFirstIterator  Octree iterator class 
COctreeFixedDepthIterator  Octree iterator class 
COctreeIteratorBase  Abstract octree iterator class 
COctreeKey  Octree key class 
COctreeLeafNode  Abstract octree leaf class 
COctreeLeafNodeBreadthFirstIterator  Octree leaf node iterator class 
COctreeLeafNodeDepthFirstIterator  Octree leaf node iterator class 
COctreeNode  Abstract octree node class 
COctreeNodePool  Octree node pool 
COctreePointCloud  Octree pointcloud class 
COctreePointCloudAdjacency  Octree pointcloud voxel class which maintains adjacency information for its voxels 
COctreePointCloudAdjacencyContainer  Octree adjacency leaf container class stores a list of pointers to neighbors, number of points added, and a DataT value 
COctreePointCloudChangeDetector  Octree pointcloud change detector class 
COctreePointCloudDensity  Octree pointcloud density class 
COctreePointCloudDensityContainer  Octree pointcloud density leaf node class 
COctreePointCloudOccupancy  Octree pointcloud occupancy class 
COctreePointCloudPointVector  Octree pointcloud point vector class 
►COctreePointCloudSearch  Octree pointcloud search class 
CprioBranchQueueEntry  Priority queue entry for branch nodes 
CprioPointQueueEntry  Priority queue entry for point candidates 
COctreePointCloudSinglePoint  Octree pointcloud single point class 
COctreePointCloudVoxelCentroid  Octree pointcloud voxel centroid class 
COctreePointCloudVoxelCentroidContainer  Octree pointcloud voxel centroid leaf node class 
CPointCoding  PointCoding class 
►Noutofcore  
COutofcoreAbstractMetadata  
COutofcoreAbstractNodeContainer  
COutofcoreBreadthFirstIterator  
COutofcoreDepthFirstIterator  
COutofcoreIteratorBase  Abstract octree iterator class 
COutofcoreOctreeBase  This code defines the octree used for point storage at Urban Robotics 
COutofcoreOctreeBaseMetadata  Encapsulated class to read JSON metadata into memory, and write the JSON metadata associated with the octree root node 
COutofcoreOctreeBaseNode  OutofcoreOctreeBaseNode Class internally representing nodes of an outofcore octree, with accessors to its data via the pcl::outofcore::OutofcoreOctreeDiskContainer class or pcl::outofcore::OutofcoreOctreeRamContainer class, whichever it is templated against 
COutofcoreOctreeDiskContainer  Class responsible for serialization and deserialization of out of core point data 
COutofcoreOctreeNodeMetadata  Encapsulated class to read JSON metadata into memory, and write the JSON metadata for each node 
COutofcoreOctreeRamContainer  Storage container class which the outofcore octree base is templated against 
COutofcoreParams  
►Npeople  
CGroundBasedPeopleDetectionApp  GroundBasedPeopleDetectionApp performs people detection on RGBD data having as input the ground plane coefficients 
CHeadBasedSubclustering  HeadBasedSubclustering represents a class for searching for people inside a HeightMap2D based on a 3D head detection algorithm 
CHeightMap2D  HeightMap2D represents a class for creating a 2D height map from a point cloud and searching for its local maxima 
CHOG  HOG represents a class for computing the HOG descriptor described in Dalal, N 
CPersonClassifier  
CPersonCluster  PersonCluster represents a class for representing information about a cluster containing a person 
►Npoisson  
CAllocator  This templated class assists in memory allocation and is well suited for instances when it is known that the sequence of memory allocations is performed in a stackbased manner, so that memory allocated last is released first 
CAllocatorState  
CBinaryNode  
►CBSplineData  
CBSplineComponents  
CBSplineElementCoefficients  
CBSplineElements  
CCoredEdgeIndex  
CCoredFileMeshData  
CCoredFileMeshData2  
CCoredMeshData  
►CCoredMeshData2  
CVertex  
CCoredPointIndex  
CCoredVectorMeshData  
CCoredVectorMeshData2  
CCoredVertexIndex  
CCube  
CEdge  
CEdgeIndex  
CFunctionData  
CMapReduceVector  
CMarchingCubes  
CMarchingSquares  
CMatrixEntry  
CMinimalAreaTriangulation  
CNVector  
►COctNode  
CConstNeighborKey3  
CConstNeighborKey5  
CConstNeighbors3  
CConstNeighbors5  
CNeighborKey3  
CNeighborKey5  
CNeighbors3  
CNeighbors5  
COctree  
CPoint3D  
CPoissonBadArgumentException  An exception that is thrown when the arguments number or type is wrong/unhandled 
CPoissonBadInitException  An exception that is thrown when initialization fails 
CPoissonException  A base class for all poisson exceptions which inherits from std::runtime_error 
CPoissonOpenMPException  An exception that is thrown when something goes wrong inside an openMP for loop 
CPolynomial  
CPPolynomial  
CRootInfo  
►CSortedTreeNodes  
CCornerIndices  
CCornerTableData  
CEdgeIndices  
CEdgeTableData  
CSparseMatrix  
CSparseSymmetricMatrix  
CSquare  
CStartingPolynomial  
CTreeNodeData  
CTriangle  
CTriangleIndex  
CTriangulation  
CTriangulationEdge  
CTriangulationTriangle  
CUpSampleData  
CVector  
CVertexData  
►Nrecognition  
►CBVH  This class is an implementation of bounding volume hierarchies 
CBoundedObject  
CNode  
CHoughSpace3D  HoughSpace3D is a 3D voting space 
CHypothesis  
CHypothesisBase  
►CModelLibrary  
CModel  Stores some information about the model 
►CObjRecRANSAC  This is a RANSACbased 3D object recognition method 
CHypothesisCreator  
COrientedPointPair  
COutput  This is an output item of the ObjRecRANSAC::recognize() method 
►CORRGraph  
CNode  
►CORROctree  That's a very specialized and simple octree class 
►CNode  
CData  
►CORROctreeZProjection  
CPixel  
CSet  
CRigidTransformSpace  
CRotationSpace  This is a class for a discrete representation of the rotation space based on the axisangle representation 
►CRotationSpaceCell  
CEntry  
CRotationSpaceCellCreator  
CRotationSpaceCreator  
►CSimpleOctree  
CNode  
CTrimmedICP  
CVoxelStructure  This class is a box in R3 built of voxels ordered in a regular rectangular grid 
►Nregistration  
Cby_score  Sorting of candidates based on fitness score value 
CConvergenceCriteria  ConvergenceCriteria represents an abstract base class for different convergence criteria used in registration loops 
CCorrespondenceEstimation  CorrespondenceEstimation represents the base class for determining correspondences between target and query point sets/features 
CCorrespondenceEstimationBackProjection  CorrespondenceEstimationBackprojection computes correspondences as points in the target cloud which have minimum 
CCorrespondenceEstimationBase  Abstract CorrespondenceEstimationBase class 
CCorrespondenceEstimationNormalShooting  CorrespondenceEstimationNormalShooting computes correspondences as points in the target cloud which have minimum distance to normals computed on the input cloud 
CCorrespondenceEstimationOrganizedProjection  CorrespondenceEstimationOrganizedProjection computes correspondences by projecting the source point cloud onto the target point cloud using the camera intrinsic and extrinsic parameters 
CCorrespondenceRejectionOrganizedBoundary  Implements a simple correspondence rejection measure 
CCorrespondenceRejector  CorrespondenceRejector represents the base class for correspondence rejection methods 
CCorrespondenceRejectorDistance  CorrespondenceRejectorDistance implements a simple correspondence rejection method based on thresholding the distances between the correspondences 
►CCorrespondenceRejectorFeatures  CorrespondenceRejectorFeatures implements a correspondence rejection method based on a set of feature descriptors 
CFeatureContainer  An inner class containing pointers to the source and target feature clouds and the parameters needed to perform the correspondence search 
CFeatureContainerInterface  
CCorrespondenceRejectorMedianDistance  CorrespondenceRejectorMedianDistance implements a simple correspondence rejection method based on thresholding based on the median distance between the correspondences 
CCorrespondenceRejectorOneToOne  CorrespondenceRejectorOneToOne implements a correspondence rejection method based on eliminating duplicate match indices in the correspondences 
CCorrespondenceRejectorPoly  CorrespondenceRejectorPoly implements a correspondence rejection method that exploits lowlevel and poseinvariant geometric constraints between two point sets by forming virtual polygons of a userspecifiable cardinality on each model using the input correspondences 
CCorrespondenceRejectorSampleConsensus  CorrespondenceRejectorSampleConsensus implements a correspondence rejection using Random Sample Consensus to identify inliers (and reject outliers) 
CCorrespondenceRejectorSampleConsensus2D  CorrespondenceRejectorSampleConsensus2D implements a pixelbased correspondence rejection using Random Sample Consensus to identify inliers (and reject outliers) 
CCorrespondenceRejectorSurfaceNormal  CorrespondenceRejectorSurfaceNormal implements a simple correspondence rejection method based on the angle between the normals at correspondent points 
CCorrespondenceRejectorTrimmed  CorrespondenceRejectorTrimmed implements a correspondence rejection for ICPlike registration algorithms that uses only the best 'k' correspondences where 'k' is some estimate of the overlap between the two point clouds being registered 
CCorrespondenceRejectorVarTrimmed  CorrespondenceRejectoVarTrimmed implements a simple correspondence rejection method by considering as inliers a certain percentage of correspondences with the least distances 
CDataContainer  DataContainer is a container for the input and target point clouds and implements the interface to compute correspondence scores between correspondent points in the input and target clouds 
CDataContainerInterface  DataContainerInterface provides a generic interface for computing correspondence scores between correspondent points in the input and target clouds 
CDefaultConvergenceCriteria  DefaultConvergenceCriteria represents an instantiation of ConvergenceCriteria, and implements the following criteria for registration loop evaluation: 
►CELCH  ELCH (Explicit Loop Closing Heuristic) class 
CVertex  
CFPCSInitialAlignment  FPCSInitialAlignment computes corresponding four point congruent sets as described in: "4points congruent sets for robust pairwise surface registration", Dror Aiger, Niloy Mitra, Daniel CohenOr 
CGraphHandler  GraphHandler class is a wrapper for a general SLAM graph The actual graph class must fulfill the following boost::graph concepts: 
CGraphOptimizer  GraphOptimizer class; derive and specialize for each graph type 
CIncrementalRegistration  Incremental IterativeClosestPoint class 
CKFPCSInitialAlignment  KFPCSInitialAlignment computes corresponding four point congruent sets based on keypoints as described in: "Markerless point cloud registration with keypointbased 4points congruent sets", Pascal Theiler, Jan Dirk Wegner, Konrad Schindler 
►CLUM  Globally Consistent Scan Matching based on an algorithm by Lu and Milios 
CEdgeProperties  
CVertexProperties  
CMatchingCandidate  Container for matching candidate consisting of 
CMetaRegistration  Meta Registration class 
CNullEstimate  NullEstimate struct 
CNullMeasurement  NullMeasurement struct 
CPoseEstimate  PoseEstimate struct 
CPoseMeasurement  PoseMeasurement struct 
CsortCorrespondencesByDistance  sortCorrespondencesByDistance : a functor for sorting correspondences by distance 
CsortCorrespondencesByMatchIndex  sortCorrespondencesByMatchIndex : a functor for sorting correspondences by match index 
CsortCorrespondencesByMatchIndexAndDistance  sortCorrespondencesByMatchIndexAndDistance : a functor for sorting correspondences by match index and distance 
CsortCorrespondencesByQueryIndex  sortCorrespondencesByQueryIndex : a functor for sorting correspondences by query index 
CsortCorrespondencesByQueryIndexAndDistance  sortCorrespondencesByQueryIndexAndDistance : a functor for sorting correspondences by query index and distance 
CTransformationEstimation  TransformationEstimation represents the base class for methods for transformation estimation based on: 
CTransformationEstimation2D  TransformationEstimation2D implements a simple 2D rigid transformation estimation (x, y, theta) for a given pair of datasets 
CTransformationEstimation3Point  TransformationEstimation3Points represents the class for transformation estimation based on: 
CTransformationEstimationDQ  TransformationEstimationDQ implements dual quaternion based estimation of the transformation aligning the given correspondences 
CTransformationEstimationDualQuaternion  TransformationEstimationDualQuaternion implements dual quaternion based estimation of the transformation aligning the given correspondences 
►CTransformationEstimationLM  TransformationEstimationLM implements Levenberg Marquardtbased estimation of the transformation aligning the given correspondences 
CFunctor  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 
COptimizationFunctor  
COptimizationFunctorWithIndices  
CTransformationEstimationPointToPlane  TransformationEstimationPointToPlane uses Levenberg Marquardt optimization to find the transformation that minimizes the pointtoplane distance between the given correspondences 
CTransformationEstimationPointToPlaneLLS  TransformationEstimationPointToPlaneLLS implements a Linear Least Squares (LLS) approximation for minimizing the pointtoplane distance between two clouds of corresponding points with normals 
CTransformationEstimationPointToPlaneLLSWeighted  TransformationEstimationPointToPlaneLLSWeighted implements a Linear Least Squares (LLS) approximation for minimizing the pointtoplane distance between two clouds of corresponding points with normals, with the possibility of assigning weights to the correspondences 
►CTransformationEstimationPointToPlaneWeighted  TransformationEstimationPointToPlaneWeighted uses Levenberg Marquardt optimization to find the transformation that minimizes the pointtoplane distance between the given correspondences 
CFunctor  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 
COptimizationFunctor  
COptimizationFunctorWithIndices  
CTransformationEstimationSVD  TransformationEstimationSVD implements SVDbased estimation of the transformation aligning the given correspondences 
CTransformationEstimationSVDScale  TransformationEstimationSVD implements SVDbased estimation of the transformation aligning the given correspondences 
CTransformationValidation  TransformationValidation represents the base class for methods that validate the correctness of a transformation found through TransformationEstimation 
►CTransformationValidationEuclidean  TransformationValidationEuclidean computes an L2SQR norm between a source and target dataset 
CMyPointRepresentation  Internal point representation uses only 3D coordinates for L2 
CWarpPointRigid  Base warp point class 
CWarpPointRigid3D  WarpPointRigid3D enables 3D (1D rotation + 2D translation) transformations for points 
CWarpPointRigid6D  WarpPointRigid3D enables 6D (3D rotation + 3D translation) transformations for points 
►Nsearch  
CBruteForce  Implementation of a simple brute force search algorithm 
►CFlannSearch  search::FlannSearch is a generic FLANN wrapper class for the new search interface 
CFlannIndexCreator  Helper class that creates a FLANN index from a given FLANN matrix 
CKdTreeIndexCreator  Creates a FLANN KdTreeSingleIndex from the given input data 
CKdTreeMultiIndexCreator  Creates a FLANN KdTreeIndex of multiple randomized trees from the given input data, suitable for feature matching 
CKMeansIndexCreator  Creates a FLANN KdTreeSingleIndex from the given input data 
CKdTree  search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search functions using KdTree structure 
COctree  search::Octree is a wrapper class which implements nearest neighbor search operations based on the pcl::octree::Octree structure 
►COrganizedNeighbor  OrganizedNeighbor is a class for optimized nearest neigbhor search in organized point clouds 
CEntry  
CSearch  Generic search class 
►Nsegmentation  
►Ndetail  
CRandomWalker  Multilabel graph segmentation using random walks 
►Ngrabcut  
CBoykovKolmogorov  Boost implementation of Boykov and Kolmogorov's maxflow algorithm doesn't support negative flows which makes it inappropriate for this context 
CColor  Structure to save RGB colors into floats 
CGaussian  Gaussian structure 
CGaussianFitter  Helper class that fits a single Gaussian to color samples 
CGMM  
►Nsurface  
CSimplificationRemoveUnusedVertices  
►Ntest  Test_macros.h provide helper macros for testing vectors, matrices etc 
►Ntexture_mapping  
CCamera  Structure to store camera pose and focal length 
CUvIndex  Structure that links a uv coordinate to its 3D point and face 
►Ntracking  
C_ParticleXYR  
C_ParticleXYRP  
C_ParticleXYRPY  
C_ParticleXYZR  
C_ParticleXYZRPY  
CApproxNearestPairPointCloudCoherence  ApproxNearestPairPointCloudCoherence computes coherence between two pointclouds using the approximate nearest point pairs 
CDistanceCoherence  DistanceCoherence computes coherence between two points from the distance between them 
CHSVColorCoherence  HSVColorCoherence computes coherence between the two points from the color difference between them 
CKLDAdaptiveParticleFilterOMPTracker  KLDAdaptiveParticleFilterOMPTracker tracks the PointCloud which is given by setReferenceCloud within the measured PointCloud using particle filter method 
CKLDAdaptiveParticleFilterTracker  KLDAdaptiveParticleFilterTracker tracks the PointCloud which is given by setReferenceCloud within the measured PointCloud using particle filter method 
CNearestPairPointCloudCoherence  NearestPairPointCloudCoherence computes coherence between two pointclouds using the nearest point pairs 
CNormalCoherence  NormalCoherence computes coherence between two points from the angle between their normals 
CParticleFilterOMPTracker  ParticleFilterOMPTracker tracks the PointCloud which is given by setReferenceCloud within the measured PointCloud using particle filter method in parallel, using the OpenMP standard 
CParticleFilterTracker  ParticleFilterTracker tracks the PointCloud which is given by setReferenceCloud within the measured PointCloud using particle filter method 
CParticleXYR  
CParticleXYRP  
CParticleXYRPY  
CParticleXYZR  
CParticleXYZRPY  
CPointCloudCoherence  PointCloudCoherence is a base class to compute coherence between the two PointClouds 
CPointCoherence  PointCoherence is a base class to compute coherence between the two points 
CPyramidalKLTTracker  Pyramidal Kanade Lucas Tomasi tracker 
CRGBValue  
CTracker  Tracker represents the base tracker class 
►Ntraits  
CasEnum  
CasEnum< double >  
CasEnum< float >  
CasEnum< int16_t >  
CasEnum< int32_t >  
CasEnum< int8_t >  
CasEnum< uint16_t >  
CasEnum< uint32_t >  
CasEnum< uint8_t >  
CasType  
CasType< pcl::PCLPointField::FLOAT32 >  
CasType< pcl::PCLPointField::FLOAT64 >  
CasType< pcl::PCLPointField::INT16 >  
CasType< pcl::PCLPointField::INT32 >  
CasType< pcl::PCLPointField::INT8 >  
CasType< pcl::PCLPointField::UINT16 >  
CasType< pcl::PCLPointField::UINT32 >  
CasType< pcl::PCLPointField::UINT8 >  
Cdatatype  
CdecomposeArray  
CfieldList  
Cname  
Coffset  
CPOD  
►Nvisualization  
►Ncontext_items  
CCircle  
CDisk  
CFilledRectangle  
CLine  
CMarkers  
CPoint  
CPoints  
CPolygon  
CRectangle  
CText  
CAreaPickingEvent  /brief Class representing 3D area picking events 
CCamera  Camera class holds a set of camera parameters together with the window pos/size 
CCloudActor  
CCloudViewer  Simple point cloud visualization class 
CFEllipticArc2D  Class for storing EllipticArc; every ellipse , circle are covered by this 
CFigure2D  Abstract class for storing figure information 
CFloatImageUtils  Provide some gerneral functionalities regarding 2d float arrays, e.g., for visualization purposes 
CFPoints2D  Class for storing Points 
CFPolygon2D  Class for Polygon 
CFPolyLine2D  Class for PolyLine 
CFQuad2D  Class for storing Quads 
►CImageViewer  ImageViewer is a class for 2D image visualization 
CExitCallback  
CExitMainLoopTimerCallback  
CImageViewerInteractorStyle  An image viewer interactor style, tailored for ImageViewer 
CKeyboardEvent  /brief Class representing key hit/release events 
CMouseEvent  
CPCLContextImageItem  Struct PCLContextImageItem a specification of vtkContextItem, used to add an image to the scene in the ImageViewer class 
CPCLContextItem  Struct PCLContextItem represents our own custom version of vtkContextItem, used by the ImageViewer class 
CPCLHistogramVisualizer  PCL histogram visualizer main class 
CPCLHistogramVisualizerInteractorStyle  PCL histogram visualizer interactory style class 
CPCLImageCanvasSource2D  PCLImageCanvasSource2D represents our own custom version of vtkImageCanvasSource2D, used by the ImageViewer class 
CPCLPainter2D  PCL Painter2D main class 
CPCLPlotter  PCL Plotter main class 
CPCLSimpleBufferVisualizer  PCL simple buffer visualizer main class 
CPCLVisualizer  PCL Visualizer main class 
CPCLVisualizerInteractorStyle  PCLVisualizerInteractorStyle defines an unique, custom VTK based interactory style for PCL Visualizer applications 
CPointCloudColorHandler  Base Handler class for PointCloud colors 
CPointCloudColorHandler< pcl::PCLPointCloud2 >  Base Handler class for PointCloud colors 
CPointCloudColorHandlerCustom  Handler for predefined user colors 
CPointCloudColorHandlerCustom< pcl::PCLPointCloud2 >  Handler for predefined user colors 
CPointCloudColorHandlerGenericField  Generic field handler class for colors 
CPointCloudColorHandlerGenericField< pcl::PCLPointCloud2 >  Generic field handler class for colors 
CPointCloudColorHandlerHSVField  HSV handler class for colors 
CPointCloudColorHandlerHSVField< pcl::PCLPointCloud2 >  HSV handler class for colors 
CPointCloudColorHandlerLabelField  Label field handler class for colors 
CPointCloudColorHandlerLabelField< pcl::PCLPointCloud2 >  Label field handler class for colors 
CPointCloudColorHandlerRandom  Handler for random PointCloud colors (i.e., R, G, B will be randomly chosen) 
CPointCloudColorHandlerRandom< pcl::PCLPointCloud2 >  Handler for random PointCloud colors (i.e., R, G, B will be randomly chosen) 
CPointCloudColorHandlerRGBAField  RGBA handler class for colors 
CPointCloudColorHandlerRGBAField< pcl::PCLPointCloud2 >  RGBA handler class for colors 
CPointCloudColorHandlerRGBField  RGB handler class for colors 
CPointCloudColorHandlerRGBField< pcl::PCLPointCloud2 >  RGB handler class for colors 
CPointCloudColorHandlerRGBHack  
CPointCloudGeometryHandler  Base handler class for PointCloud geometry 
CPointCloudGeometryHandler< pcl::PCLPointCloud2 >  Base handler class for PointCloud geometry 
CPointCloudGeometryHandlerCustom  Custom handler class for PointCloud geometry 
CPointCloudGeometryHandlerCustom< pcl::PCLPointCloud2 >  Custom handler class for PointCloud geometry 
CPointCloudGeometryHandlerSurfaceNormal  Surface normal handler class for PointCloud geometry 
CPointCloudGeometryHandlerSurfaceNormal< pcl::PCLPointCloud2 >  Surface normal handler class for PointCloud geometry 
CPointCloudGeometryHandlerXYZ  XYZ handler class for PointCloud geometry 
CPointCloudGeometryHandlerXYZ< pcl::PCLPointCloud2 >  XYZ handler class for PointCloud geometry 
CPointPickingCallback  
CPointPickingEvent  /brief Class representing 3D point picking events 
CRangeImageVisualizer  Range image visualizer class 
CRenWinInteract  
►CWindow  
CExitCallback  
CExitMainLoopTimerCallback  
C_Axis  
C_Intensity  
C_Intensity32u  
C_Intensity8u  
C_Normal  
C_PointDEM  
C_PointNormal  
C_PointSurfel  
C_PointWithRange  
C_PointWithScale  
C_PointWithViewpoint  
C_PointXYZ  
C_PointXYZHSV  
C_PointXYZI  A point structure representing Euclidean xyz coordinates, and the intensity value 
C_PointXYZINormal  
C_PointXYZL  
C_PointXYZLAB  
C_PointXYZLNormal  
C_PointXYZRGB  
C_PointXYZRGBA  
C_PointXYZRGBL  
C_PointXYZRGBNormal  
C_ReferenceFrame  A structure representing the Local Reference Frame of a point 
C_RGB  
CAdaptiveCostSOStereoMatching  Adaptive Cost 2pass Scanline Optimization Stereo Matching class 
CAdaptiveRangeCoder  AdaptiveRangeCoder compression class 
CAgastKeypoint2D  Detects 2D AGAST corner points 
CAgastKeypoint2D< pcl::PointXYZ, pcl::PointUV >  Detects 2D AGAST corner points 
CAgastKeypoint2DBase  Detects 2D AGAST corner points 
CApproximateProgressiveMorphologicalFilter  Implements the Progressive Morphological Filter for segmentation of ground points 
CApproximateVoxelGrid  ApproximateVoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data 
CASCIIReader  Ascii Point Cloud Reader 
CAxis  A point structure representing an Axis using its normal coordinates 
CBadArgumentException  An exception that is thrown when the arguments number or type is wrong/unhandled 
CBearingAngleImage  Class BearingAngleImage is used as an interface to generate Bearing Angle(BA) image 
CBilateralFilter  A bilateral filter implementation for point cloud data 
CBilateralUpsampling  Bilateral filtering implementation, based on the following paper: 
CBinaryTreeThresholdBasedBranchEstimator  Branch estimator for binary trees where the branch is computed only from the threshold 
CBivariatePolynomialT  This represents a bivariate polynomial and provides some functionality for it 
CBlockBasedStereoMatching  Block based (or fixed window) Stereo Matching class 
CBOARDLocalReferenceFrameEstimation  BOARDLocalReferenceFrameEstimation implements the BOrder Aware Repeatable Directions algorithm for local reference frame estimation as described here: 
CBorderDescription  A structure to store if a point in a range image lies on a border between an obstacle and the background 
CBoundary  A point structure representing a description of whether a point is lying on a surface boundary or not 
CBoundaryEstimation  BoundaryEstimation estimates whether a set of points is lying on surface boundaries using an angle criterion 
CBoundingBoxXYZ  
CBoxClipper3D  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 
CBranchEstimator  Interface for branch estimators 
CBRISK2DEstimation  Implementation of the BRISKdescriptor, based on the original code and paper reference by 
CBriskKeypoint2D  Detects BRISK interest points based on the original code and paper reference by 
CBRISKSignature512  A point structure representing the Binary Robust Invariant Scalable Keypoints (BRISK) 
CCentroidPoint  A generic class that computes the centroid of points fed to it 
CClipper3D  Base class for 3D clipper objects 
CCloudIterator  Iterator class for point clouds with or without given indices 
CCloudSurfaceProcessing  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 
►CColorGradientDOTModality  
CCandidate  
►CColorGradientModality  Modality based on maxRGB gradients 
CCandidate  Candidate for a feature (used in feature extraction methods) 
CColorLUT  
►CColorModality  
CCandidate  
CComparator  Comparator is the base class for comparators that compare two points given some function 
CComparisonBase  The (abstract) base class for the comparison object 
CComputeFailedException  
CConcaveHull  ConcaveHull (alpha shapes) using libqhull library 
CConditionalEuclideanClustering  ConditionalEuclideanClustering performs segmentation based on Euclidean distance and a userdefined clustering condition 
CConditionalRemoval  ConditionalRemoval filters data that satisfies certain conditions 
CConditionAnd  AND condition 
CConditionBase  Base condition class 
CConditionOr  OR condition 
►CConstCloudIterator  Iterator class for point clouds with or without given indices 
CConstIteratorIdx  
CDefaultConstIterator  
CConvexHull  ConvexHull using libqhull library 
CConvolution  A 2D convolution class 
CCopyIfFieldExists  A helper functor that can copy a specific value if the given field exists 
CCorrespondence  Correspondence represents a match between two entities (e.g., points, descriptors, etc) 
CCorrespondenceGrouping  Abstract base class for Correspondence Grouping algorithms 
CCovarianceSampling  Point Cloud sampling based on the 6D covariances 
CCPCSegmentation  A segmentation algorithm partitioning a supervoxel graph 
CCPPFEstimation  Class that calculates the "surflet" features for each pair in the given pointcloud 
CCPPFSignature  A point structure for storing the Point Pair Feature (CPPF) values 
CCrfNormalSegmentation  
CCrfSegmentation  
CCRHAlignment  CRHAlignment uses two Camera Roll Histograms (CRH) to find the roll rotation that aligns both views 
CCRHEstimation  CRHEstimation estimates the Camera Roll Histogram (CRH) descriptor for a given point cloud dataset containing XYZ data and normals, as presented in: 
CCropBox  CropBox is a filter that allows the user to filter all the data inside of a given box 
CCropBox< pcl::PCLPointCloud2 >  CropBox is a filter that allows the user to filter all the data inside of a given box 
CCropHull  Filter points that lie inside or outside a 3D closed surface or 2D closed polygon, as generated by the ConvexHull or ConcaveHull classes 
CCustomPointRepresentation  CustomPointRepresentation extends PointRepresentation to allow for subpart selection on the point 
CCVFHEstimation  CVFHEstimation estimates the Clustered Viewpoint Feature Histogram (CVFH) descriptor for a given point cloud dataset containing XYZ data and normals, as presented in: 
CDavidSDKGrabber  Grabber for davidSDK structured light compliant devices 
CDecisionForest  Class representing a decision forest 
CDecisionForestEvaluator  Utility class for evaluating a decision forests 
CDecisionForestTrainer  Trainer for decision trees 
CDecisionTree  Class representing a decision tree 
CDecisionTreeEvaluator  Utility class for evaluating a decision tree 
CDecisionTreeTrainer  Trainer for decision trees 
CDecisionTreeTrainerDataProvider  
CDefaultFeatureRepresentation  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) 
CDefaultIterator  
CDefaultPointRepresentation  DefaultPointRepresentation extends PointRepresentation to define default behavior for common point types 
CDefaultPointRepresentation< FPFHSignature33 >  
CDefaultPointRepresentation< GASDSignature512 >  
CDefaultPointRepresentation< GASDSignature7992 >  
CDefaultPointRepresentation< GASDSignature984 >  
CDefaultPointRepresentation< Narf36 >  
CDefaultPointRepresentation< NormalBasedSignature12 >  
CDefaultPointRepresentation< PFHRGBSignature250 >  
CDefaultPointRepresentation< PFHSignature125 >  
CDefaultPointRepresentation< PointNormal >  
CDefaultPointRepresentation< PointXYZ >  
CDefaultPointRepresentation< PointXYZI >  
CDefaultPointRepresentation< PPFSignature >  
CDefaultPointRepresentation< ShapeContext1980 >  
CDefaultPointRepresentation< SHOT1344 >  
CDefaultPointRepresentation< SHOT352 >  
CDefaultPointRepresentation< UniqueShapeContext1960 >  
CDefaultPointRepresentation< VFHSignature308 >  
CDenseCrf  
CDenseQuantizedMultiModTemplate  
CDenseQuantizedSingleModTemplate  
CDepthSenseGrabber  Grabber for DepthSense devices (e.g 
CDifferenceOfNormalsEstimation  A Difference of Normals (DoN) scale filter implementation for point cloud data 
CDigitalElevationMapBuilder  Build a Digital Elevation Map in the columndisparity space from a disparity map and a color image of the scene 
CDinastGrabber  Grabber for DINAST devices (i.e., IPA1002, IPA1110, IPA2001) 
CDisparityMapConverter  Compute point cloud from the disparity map 
CDistanceMap  Represents a distance map obtained from a distance transformation 
CDOTMOD  Template matching using the DOTMOD approach 
CDOTModality  
CDOTMODDetection  
CEarClipping  The ear clipping triangulation algorithm 
CEdge  
CEdgeAwarePlaneComparator  EdgeAwarePlaneComparator is a Comparator that operates on plane coefficients, for use in planar segmentation 
CEnergyMaps  Stores a set of energy maps 
CEnsensoGrabber  Grabber for IDSImaging Ensenso's devices 
CESFEstimation  ESFEstimation estimates the ensemble of shape functions descriptors for a given point cloud dataset containing points 
CESFSignature640  A point structure representing the Ensemble of Shape Functions (ESF) 
CEuclideanClusterComparator  EuclideanClusterComparator is a comparator used for finding clusters based on euclidian distance 
CEuclideanClusterComparator< PointT, PointLT, deprecated::T >  
CEuclideanClusterExtraction  EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense 
CEuclideanPlaneCoefficientComparator  EuclideanPlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation 
CEventFrequency  A helper class to measure frequency of a certain event 
CExtractIndices  ExtractIndices extracts a set of indices from a point cloud 
CExtractIndices< pcl::PCLPointCloud2 >  ExtractIndices extracts a set of indices from a point cloud 
CExtractPolygonalPrismData  ExtractPolygonalPrismData uses a set of point indices that represent a planar model, and together with a given height, generates a 3D polygonal prism 
►CFastBilateralFilter  Implementation of a fast bilateral filter for smoothing depth information in organized point clouds Based on the following paper: 
CArray3D  
CFastBilateralFilterOMP  Implementation of a fast bilateral filter for smoothing depth information in organized point clouds Based on the following paper: 
CFeature  Feature represents the base feature class 
CFeatureFromLabels  
CFeatureFromNormals  
CFeatureHandler  Utility class interface which is used for creating and evaluating features 
CFeatureHistogram  Type for histograms for computing mean and variance of some floats 
CFeatureWithLocalReferenceFrames  FeatureWithLocalReferenceFrames provides a public interface for descriptor extractor classes which need a local reference frame at each input keypoint 
CFern  Class representing a Fern 
CFernEvaluator  Utility class for evaluating a fern 
CFernTrainer  Trainer for a Fern 
CFieldComparison  The fieldbased specialization of the comparison object 
CFieldMatches  
CFileGrabber  FileGrabber provides a containerstyle interface for grabbers which operate on fixedsize input 
CFileReader  Point Cloud Data (FILE) file format reader interface 
CFileWriter  Point Cloud Data (FILE) file format writer 
CFilter  Filter represents the base filter class 
CFilter< pcl::PCLPointCloud2 >  Filter represents the base filter class 
CFilterIndices  FilterIndices represents the base class for filters that are about binary point removal 
CFilterIndices< pcl::PCLPointCloud2 >  FilterIndices represents the base class for filters that are about binary point removal 
CFLARELocalReferenceFrameEstimation  FLARELocalReferenceFrameEstimation implements the Fast LocAl Reference framE algorithm for local reference frame estimation as described here: 
Cfor_each_type_impl  
Cfor_each_type_impl< false >  
CFPFHEstimation  FPFHEstimation estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud dataset containing points and normals 
CFPFHEstimationOMP  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 
CFPFHSignature33  A point structure representing the Fast Point Feature Histogram (FPFH) 
CFrustumCulling  FrustumCulling filters points inside a frustum given by pose and field of view of the camera 
CFunctor  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 
CGASDColorEstimation  GASDColorEstimation estimates the Globally Aligned Spatial Distribution (GASD) descriptor for a given point cloud dataset given XYZ and RGB data 
CGASDEstimation  GASDEstimation estimates the Globally Aligned Spatial Distribution (GASD) descriptor for a given point cloud dataset given XYZ data 
CGASDSignature512  A point structure representing the Globally Aligned Spatial Distribution (GASD) shape descriptor 
CGASDSignature7992  A point structure representing the Globally Aligned Spatial Distribution (GASD) shape and color descriptor 
CGASDSignature984  A point structure representing the Globally Aligned Spatial Distribution (GASD) shape and color descriptor 
CGaussianKernel  Class GaussianKernel assembles all the method for computing, convolving, smoothing, gradients computing an image using a gaussian kernel 
►CGeneralizedIterativeClosestPoint  GeneralizedIterativeClosestPoint is an ICP variant that implements the generalized iterative closest point algorithm as described by Alex Segal et al 
COptimizationFunctorWithIndices  Optimization functor structure 
CGeometricConsistencyGrouping  Class implementing a 3D correspondence grouping enforcing geometric consistency among feature correspondences 
CGFPFHEstimation  GFPFHEstimation estimates the Global Fast Point Feature Histogram (GFPFH) descriptor for a given point cloud dataset containing points and labels 
CGFPFHSignature16  A point structure representing the GFPFH descriptor with 16 bins 
CGlobalHypothesesVerification  A hypothesis verification method proposed in "A Global Hypotheses Verification Method for 3D Object Recognition", A 
CGrabber  Grabber interface for PCL 1.x device drivers 
►CGrabCut  Implementation of the GrabCut segmentation in "GrabCut â€” Interactive Foreground Extraction using Iterated Graph Cuts" by Carsten Rother, Vladimir Kolmogorov and Andrew Blake 
CNLinks  
CGradientXY  A point structure representing Euclidean xyz coordinates, and the intensity value 
CGraphRegistration  GraphRegistration class is the base class for graphbased registration methods 
CGrayStereoMatching  Stereo Matching abstract class for Grayscale images 
CGreedyProjectionTriangulation  GreedyProjectionTriangulation is an implementation of a greedy triangulation algorithm for 3D points based on local 2D projections 
CGreedyVerification  A greedy hypothesis verification method 
CGridMinimum  GridMinimum assembles a local 2D grid over a given PointCloud, and downsamples the data 
►CGridProjection  Grid projection surface reconstruction method 
CLeaf  Data leaf 
CGroundPlaneComparator  GroundPlaneComparator is a Comparator for detecting smooth surfaces suitable for driving 
CGRSDEstimation  GRSDEstimation estimates the Global Radiusbased Surface Descriptor (GRSD) for a given point cloud dataset containing points and normals 
CGRSDSignature21  A point structure representing the Global Radiusbased Surface Descriptor (GRSD) 
CHarrisKeypoint2D  HarrisKeypoint2D detects Harris corners family points 
CHarrisKeypoint3D  HarrisKeypoint3D uses the idea of 2D Harris keypoints, but instead of using image gradients, it uses surface normals 
CHarrisKeypoint6D  Keypoint detector for detecting corners in 3D (XYZ), 2D (intensity) AND mixed versions of these 
CHashTableOLD  
►CHDLGrabber  Grabber for the Velodyne HighDefinitionLaser (HDL) 
CHDLDataPacket  
CHDLFiringData  
CHDLLaserCorrection  
CHDLLaserReturn  
CHistogram  A point structure representing an ND histogram 
CHough3DGrouping  Class implementing a 3D correspondence grouping algorithm that can deal with multiple instances of a model template found into a given scene 
CHypothesisVerification  Abstract class for hypotheses verification methods 
CIFSReader  Indexed Face set (IFS) file format reader 
CIFSWriter  Point Cloud Data (IFS) file format writer 
CImageGrabber  
CImageGrabberBase  Base class for Image file grabber 
CInitFailedException  An exception thrown when init can not be performed should be used in all the PCLBase class inheritants 
CIntegralImage2D  Determines an integral image representation for a given organized data array 
CIntegralImage2D< DataType, 1 >  Partial template specialization for integral images with just one channel 
CIntegralImageNormalEstimation  Surface normal estimation on organized data using integral images 
CIntegralImageTypeTraits  
CIntegralImageTypeTraits< char >  
CIntegralImageTypeTraits< float >  
CIntegralImageTypeTraits< int >  
CIntegralImageTypeTraits< short >  
CIntegralImageTypeTraits< unsigned char >  
CIntegralImageTypeTraits< unsigned int >  
CIntegralImageTypeTraits< unsigned short >  
CIntensity  A point structure representing the grayscale intensity in singlechannel images 
CIntensity32u  A point structure representing the grayscale intensity in singlechannel images 
CIntensity8u  A point structure representing the grayscale intensity in singlechannel images 
CIntensityGradient  A point structure representing the intensity gradient of an XYZI point cloud 
CIntensityGradientEstimation  IntensityGradientEstimation estimates the intensity gradient for a point cloud that contains position and intensity values 
CIntensitySpinEstimation  IntensitySpinEstimation estimates the intensitydomain spin image descriptors for a given point cloud dataset containing points and intensity 
CInterestPoint  A point structure representing an interest point with Euclidean xyz coordinates, and an interest value 
Cintersect  
CInvalidConversionException  An exception that is thrown when a PCLPointCloud2 message cannot be converted into a PCL type 
CInvalidSACModelTypeException  An exception that is thrown when a sample consensus model doesn't have the correct number of samples defined in model_types.h 
CIOException  An exception that is thrown during an IO error (typical read/write errors) 
CISMPeak  This struct is used for storing peak 
CIsNotDenseException  An exception that is thrown when a PointCloud is not dense but is attempted to be used as dense 
CISSKeypoint3D  ISSKeypoint3D detects the Intrinsic Shape Signatures keypoints for a given point cloud 
CIterativeClosestPoint  IterativeClosestPoint provides a base implementation of the Iterative Closest Point algorithm 
CIterativeClosestPointNonLinear  IterativeClosestPointNonLinear is an ICP variant that uses LevenbergMarquardt optimization backend 
CIterativeClosestPointWithNormals  IterativeClosestPointWithNormals is a special case of IterativeClosestPoint, that uses a transformation estimated based on Point to Plane distances by default 
CIteratorIdx  
CJointIterativeClosestPoint  JointIterativeClosestPoint extends ICP to multiple frames which share the same transform 
CKdTree  KdTree represents the base spatial locator class for kdtree implementations 
CKdTreeFLANN  KdTreeFLANN is a generic type of 3D spatial locator using kDtree structures 
Ckernel  
CKernelWidthTooSmallException  An exception that is thrown when the kernel size is too small 
CKeypoint  Keypoint represents the base class for key points 
CKmeans  Kmeans clustering 
CLabel  
CLabeledEuclideanClusterExtraction  LabeledEuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense, with label info 
CLCCPSegmentation  A simple segmentation algorithm partitioning a supervoxel graph into groups of locally convex connected supervoxels separated by concave borders 
CLeastMedianSquares  LeastMedianSquares represents an implementation of the LMedS (Least Median of Squares) algorithm 
CLinearizedMaps  Stores a set of linearized maps 
CLinearLeastSquaresNormalEstimation  Surface normal estimation on dense data using a leastsquares estimation based on a firstorder Taylor approximation 
CLineIterator  Organized Index Iterator for iterating over the "pixels" for a given line using the Bresenham algorithm 
CLINEMOD  Template matching using the LINEMOD approach 
CLINEMOD_OrientationMap  Map that stores orientations 
CLINEMODDetection  Represents a detection of a template using the LINEMOD approach 
►CLineRGBD  Highlevel class for template matching using the LINEMOD approach based on RGB and Depth data 
CDetection  A LineRGBD detection 
CLocalMaximum  LocalMaximum downsamples the cloud, by eliminating points that are locally maximal 
CMarchingCubes  The marching cubes surface reconstruction algorithm 
CMarchingCubesHoppe  The marching cubes surface reconstruction algorithm, using a signed distance function based on the distance from tangent planes, proposed by Hoppe et 
CMarchingCubesRBF  The marching cubes surface reconstruction algorithm, using a signed distance function based on radial basis functions 
CMaskMap  
CMaximumLikelihoodSampleConsensus  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 
CMedianFilter  Implementation of the median filter 
CMeshConstruction  MeshConstruction represents a base surface reconstruction class 
CMeshProcessing  MeshProcessing represents the base class for mesh processing algorithms 
CMeshQuadricDecimationVTK  PCL mesh decimation based on vtkQuadricDecimation from the VTK library 
CMeshSmoothingLaplacianVTK  PCL mesh smoothing based on the vtkSmoothPolyDataFilter algorithm from the VTK library 
CMeshSmoothingWindowedSincVTK  PCL mesh smoothing based on the vtkWindowedSincPolyDataFilter algorithm from the VTK library 
CMeshSubdivisionVTK  PCL mesh smoothing based on the vtkLinearSubdivisionFilter, vtkLoopSubdivisionFilter, vtkButterflySubdivisionFilter depending on the selected MeshSubdivisionVTKFilterType algorithm from the VTK library 
CMEstimatorSampleConsensus  MEstimatorSampleConsensus represents an implementation of the MSAC (Mestimator SAmple Consensus) algorithm, as described in: "MLESAC: A new robust estimator with application to estimating image geometry", P.H.S 
CMinCutSegmentation  This class implements the segmentation algorithm based on minimal cut of the graph 
►CMLSResult  Data structure used to store the results of the MLS fitting 
CMLSProjectionResults  Data structure used to store the MLS projection results 
CPolynomialPartialDerivative  Data structure used to store the MLS polynomial partial derivatives 
CModelCoefficients  
CModelOutlierRemoval  ModelOutlierRemoval filters points in a cloud based on the distance between model and point 
CMomentInvariants  A point structure representing the three moment invariants 
CMomentInvariantsEstimation  MomentInvariantsEstimation estimates the 3 moment invariants (j1, j2, j3) at each 3D point 
CMomentOfInertiaEstimation  Implements the method for extracting features based on moment of inertia 
CMorphology  
►CMovingLeastSquares  MovingLeastSquares represent an implementation of the MLS (Moving Least Squares) algorithm for data smoothing and improved normal estimation 
►CMLSVoxelGrid  A minimalistic implementation of a voxel grid, necessary for the point cloud upsampling 
CLeaf  
CMovingLeastSquaresOMP  MovingLeastSquaresOMP implementation has been merged into MovingLeastSquares for better maintainability 
CMTLReader  
CMultiChannel2DComparisonFeature  Feature for comparing two sample points in 2D multichannel data 
CMultiChannel2DComparisonFeatureHandler  Feature utility class that handles the creation and evaluation of RGBD comparison features 
CMultiChannel2DData  Holds twodimensional multichannel data 
CMultiChannel2DDataSet  Holds a set of twodimensional multichannel data 
CMultipleData2DExampleIndex  Example index for a set of 2D data blocks 
CMultiscaleFeaturePersistence  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 
►CNarf  NARF (Normal Aligned Radial Features) is a point feature descriptor type for 3D data 
CFeaturePointRepresentation  
CNarf36  A point structure representing the Narf descriptor 
►CNarfDescriptor  Computes NARF feature descriptors for points in a range image See B 
CParameters  
►CNarfKeypoint  NARF (Normal Aligned Radial Feature) keypoints 
CParameters  Parameters used in this class 
CNdCentroidFunctor  Helper functor structure for nD centroid estimation 
CNdConcatenateFunctor  Helper functor structure for concatenate 
CNdCopyEigenPointFunctor  Helper functor structure for copying data between an Eigen type and a PointT 
CNdCopyPointEigenFunctor  Helper functor structure for copying data between an Eigen type and a PointT 
CNormal  A point structure representing normal coordinates and the surface curvature estimate 
CNormalBasedSignature12  A point structure representing the Normal Based Signature for a feature matrix of 4by3 
CNormalBasedSignatureEstimation  Normalbased feature signature estimation class 
CNormalDistributionsTransform  A 3D Normal Distribution Transform registration implementation for point cloud data 
CNormalDistributionsTransform2D  NormalDistributionsTransform2D provides an implementation of the Normal Distributions Transform algorithm for scan matching 
CNormalEstimation  NormalEstimation estimates local surface properties (surface normals and curvatures)at each 3D point 
CNormalEstimationOMP  NormalEstimationOMP estimates local surface properties at each 3D point, such as surface normals and curvatures, in parallel, using the OpenMP standard 
CNormalRefinement  Normal vector refinement class 
CNormalSpaceSampling  NormalSpaceSampling samples the input point cloud in the space of normal directions computed at every point 
CNotEnoughPointsException  An exception that is thrown when the number of correspondents is not equal to the minimum required 
COBJReader  
CONIGrabber  A simple ONI grabber 
►COpenNIGrabber  Grabber for OpenNI devices (i.e., Primesense PSDK, Microsoft Kinect, Asus XTion Pro/Live) 
CmodeComp  
COrganizedConnectedComponentSegmentation  OrganizedConnectedComponentSegmentation allows connected components to be found within organized point cloud data, given a comparison function 
►COrganizedEdgeBase  OrganizedEdgeBase, OrganizedEdgeFromRGB, OrganizedEdgeFromNormals, and OrganizedEdgeFromRGBNormals find 3D edges from an organized point cloud data 
CNeighbor  
COrganizedEdgeFromNormals  
COrganizedEdgeFromRGB  
COrganizedEdgeFromRGBNormals  
COrganizedFastMesh  Simple triangulation/surface reconstruction for organized point clouds 
COrganizedIndexIterator  Base class for iterators on 2dimensional maps like images/organized clouds etc 
COrganizedMultiPlaneSegmentation  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 
►COrganizedNeighborSearch  OrganizedNeighborSearch class 
CnearestNeighborCandidate  nearestNeighborCandidate entry for the nearest neighbor candidate queue 
CradiusSearchLoopkupEntry  radiusSearchLoopkupEntry entry for radius search lookup vector 
COURCVFHEstimation  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: 
CPackedHSIComparison  A packed HSI specialization of the comparison object 
CPackedRGBComparison  A packed rgb specialization of the comparison object 
CPairwiseGraphRegistration  PairwiseGraphRegistration class aligns the clouds two by two 
CPairwisePotential  
CPapazovHV  A hypothesis verification method proposed in "An Efficient RANSAC for 3D Object Recognition in Noisy and Occluded Scenes", C 
CPassThrough  PassThrough passes points in a cloud based on constraints for one particular field of the point type 
CPassThrough< pcl::PCLPointCloud2 >  PassThrough uses the base Filter class methods to pass through all data that satisfies the user given constraints 
CPCA  Principal Component analysis (PCA) class 
CPCDGrabber  
CPCDGrabberBase  Base class for PCD file grabber 
CPCDReader  Point Cloud Data (PCD) file format reader 
CPCDWriter  Point Cloud Data (PCD) file format writer 
CPCLBase  PCL base class 
CPCLBase< pcl::PCLPointCloud2 >  
CPCLException  A base class for all pcl exceptions which inherits from std::runtime_error 
CPCLHeader  
CPCLImage  
CPCLPointCloud2  
CPCLPointField  
CPCLSurfaceBase  Pure abstract class 
►CPermutohedral  Implementation of a highdimensional gaussian filtering using the permutohedral lattice 
CNeighbors  
CPFHEstimation  PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals 
CPFHRGBEstimation  
CPFHRGBSignature250  A point structure representing the Point Feature Histogram with colors (PFHRGB) 
CPFHSignature125  A point structure representing the Point Feature Histogram (PFH) 
CPiecewiseLinearFunction  This provides functionalities to efficiently return values for piecewise linear function 
CPlanarPolygon  PlanarPolygon represents a planar (2D) polygon, potentially in a 3D space 
CPlanarPolygonFusion  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 
CPlanarRegion  PlanarRegion represents a set of points that lie in a plane 
CPlaneClipper3D  Implementation of a plane clipper in 3D 
CPlaneCoefficientComparator  PlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation 
CPlaneRefinementComparator  PlaneRefinementComparator is a Comparator that operates on plane coefficients, for use in planar segmentation 
CPLYReader  Point Cloud Data (PLY) file format reader 
CPLYWriter  Point Cloud Data (PLY) file format writer 
CPointCloud  PointCloud represents the base class in PCL for storing collections of 3D points 
CPointCorrespondence3D  Representation of a (possible) correspondence between two 3D points in two different coordinate frames (e.g 
CPointCorrespondence6D  Representation of a (possible) correspondence between two points (e.g 
CPointDataAtOffset  A datatype that enables typecorrect comparisons 
CPointDEM  A point structure representing Digital Elevation Map 
CPointIndices  
CPointNormal  A point structure representing Euclidean xyz coordinates, together with normal coordinates and the surface curvature estimate 
CPointRepresentation  PointRepresentation provides a set of methods for converting a point structs/object into an ndimensional vector 
CPointSurfel  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 
CPointUV  A 2D point structure representing pixel image coordinates 
CPointWithRange  A point structure representing Euclidean xyz coordinates, padded with an extra range float 
CPointWithScale  A point structure representing a 3D position and scale 
CPointWithViewpoint  A point structure representing Euclidean xyz coordinates together with the viewpoint from which it was seen 
CPointXY  A 2D point structure representing Euclidean xy coordinates 
CPointXY32f  2D point with float x and ycoordinates 
CPointXY32i  2D point with integer x and ycoordinates 
CPointXYZ  A point structure representing Euclidean xyz coordinates 
CPointXYZHSV  
CPointXYZI  
CPointXYZIEdge  This typedef is used to represent a point cloud containing edge information 
CPointXYZINormal  A point structure representing Euclidean xyz coordinates, intensity, together with normal coordinates and the surface curvature estimate 
CPointXYZL  
CPointXYZLAB  A custom point type for position and CIELAB color value 
CPointXYZLNormal  A point structure representing Euclidean xyz coordinates, a label, together with normal coordinates and the surface curvature estimate 
CPointXYZRGB  A point structure representing Euclidean xyz coordinates, and the RGB color 
CPointXYZRGBA  A point structure representing Euclidean xyz coordinates, and the RGBA color 
CPointXYZRGBL  
CPointXYZRGBNormal  A point structure representing Euclidean xyz coordinates, and the RGB color, together with normal coordinates and the surface curvature estimate 
CPoisson  The Poisson surface reconstruction algorithm 
CPolygonMesh  
►CPolynomialCalculationsT  This provides some functionality for polynomials, like finding roots or approximating bivariate polynomials 
CParameters  Parameters used in this class 
►CPosesFromMatches  Calculate 3D transformation based on point correspondences 
CParameters  Parameters used in this class 
►CPoseEstimate  A result of the pose estimation process 
CIsBetter  
CPPFEstimation  Class that calculates the "surflet" features for each pair in the given pointcloud 
►CPPFHashMapSearch  
CHashKeyStruct  Data structure to hold the information for the key in the feature hash map of the PPFHashMapSearch class 
►CPPFRegistration  Class that registers two point clouds based on their sets of PPFSignatures 
CPoseWithVotes  Structure for storing a pose (represented as an Eigen::Affine3f) and an integer for counting votes 
CPPFRGBEstimation  
CPPFRGBRegionEstimation  
CPPFRGBSignature  A point structure for storing the Point Pair Color Feature (PPFRGB) values 
CPPFSignature  A point structure for storing the Point Pair Feature (PPF) values 
CPrincipalCurvatures  A point structure representing the principal curvatures and their magnitudes 
CPrincipalCurvaturesEstimation  PrincipalCurvaturesEstimation estimates the directions (eigenvectors) and magnitudes (eigenvalues) of principal surface curvatures for a given point cloud dataset containing points and normals 
CPrincipalRadiiRSD  A point structure representing the minimum and maximum surface radii (in meters) computed using RSD 
CProgressiveMorphologicalFilter  Implements the Progressive Morphological Filter for segmentation of ground points 
CProgressiveSampleConsensus  RandomSampleConsensus represents an implementation of the RANSAC (RAndom SAmple Consensus) algorithm, as described in: "Matching with PROSAC â€“ Progressive Sample Consensus", Chum, O 
CProjectInliers  ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud 
CProjectInliers< pcl::PCLPointCloud2 >  ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud 
CPyramidFeatureHistogram  Class that compares two sets of features by using a multiscale representation of the features inside a pyramid 
CQuantizableModality  Interface for a quantizable modality 
CQuantizedMap  
CQuantizedMultiModFeature  Feature that defines a position and quantized value in a specific modality 
CQuantizedNormalLookUpTable  Lookuptable for fast surface normal quantization 
CRadiusOutlierRemoval  RadiusOutlierRemoval filters points in a cloud based on the number of neighbors they have 
CRadiusOutlierRemoval< 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 
CRandomizedMEstimatorSampleConsensus  RandomizedMEstimatorSampleConsensus represents an implementation of the RMSAC (Randomized Mestimator SAmple Consensus) algorithm, which basically adds a Td,d test (see RandomizedRandomSampleConsensus) to an MSAC estimator (see MEstimatorSampleConsensus) 
CRandomizedRandomSampleConsensus  RandomizedRandomSampleConsensus represents an implementation of the RRANSAC (Randomized RAndom SAmple Consensus), as described in "Randomized RANSAC with Td,d test", O 
CRandomSample  RandomSample applies a random sampling with uniform probability 
CRandomSample< pcl::PCLPointCloud2 >  RandomSample applies a random sampling with uniform probability 
CRandomSampleConsensus  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 
CRangeImage  RangeImage is derived from pcl/PointCloud and provides functionalities with focus on situations where a 3D scene was captured from a specific view point 
►CRangeImageBorderExtractor  Extract obstacle borders from range images, meaning positions where there is a transition from foreground to background 
CLocalSurface  Stores some information extracted from the neighborhood of a point 
CParameters  Parameters used in this class 
CShadowBorderIndices  Stores the indices of the shadow border corresponding to obstacle borders 
CRangeImagePlanar  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, ToFcameras), so that a conversion to point cloud and then to a spherical range image becomes unnecessary 
CRangeImageSpherical  RangeImageSpherical is derived from the original range image and uses a slightly different spherical projection 
►CRealSenseGrabber  
CMode  A descriptor for capturing mode 
CReferenceFrame  
CRegion3D  Region3D represents summary statistics of a 3D collection of points 
CRegionGrowing  Implements the well known Region Growing algorithm used for segmentation 
CRegionGrowingRGB  Implements the well known Region Growing algorithm used for segmentation based on color of points 
CRegionXY  Defines a region in XYspace 
CRegistration  Registration represents the base registration class for general purpose, ICPlike methods 
CRegistrationVisualizer  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 
CRegressionVarianceNode  Node for a regression trees which optimizes variance 
CRegressionVarianceStatsEstimator  Statistics estimator for regression trees which optimizes variance 
CRFFaceDetectorTrainer  
CRGB  A structure representing RGB color information 
CRGBPlaneCoefficientComparator  RGBPlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation 
CRIFTEstimation  RIFTEstimation estimates the Rotation Invariant Feature Transform descriptors for a given point cloud dataset containing points and intensity 
CRobotEyeGrabber  Grabber for the Ocular Robotics RobotEye sensor 
CROPSEstimation  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 
CRSDEstimation  RSDEstimation estimates the Radiusbased Surface Descriptor (minimal and maximal radius of the local surface's curves) for a given point cloud dataset containing points and normals 
CSACSegmentation  SACSegmentation represents the Nodelet segmentation class for Sample Consensus methods and models, in the sense that it just creates a Nodelet wrapper for genericpurpose SACbased segmentation 
CSACSegmentationFromNormals  SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods and models that require the use of surface normals for estimation 
CSampleConsensus  SampleConsensus represents the base class 
►CSampleConsensusInitialAlignment  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 
CErrorFunctor  
CHuberPenalty  
CTruncatedError  
CSampleConsensusModel  SampleConsensusModel represents the base model class 
CSampleConsensusModelCircle2D  SampleConsensusModelCircle2D defines a model for 2D circle segmentation on the XY plane 
CSampleConsensusModelCircle3D  SampleConsensusModelCircle3D defines a model for 3D circle segmentation 
CSampleConsensusModelCone  SampleConsensusModelCone defines a model for 3D cone segmentation 
CSampleConsensusModelCylinder  SampleConsensusModelCylinder defines a model for 3D cylinder segmentation 
CSampleConsensusModelFromNormals  SampleConsensusModelFromNormals represents the base model class for models that require the use of surface normals for estimation 
CSampleConsensusModelLine  SampleConsensusModelLine defines a model for 3D line segmentation 
CSampleConsensusModelNormalParallelPlane  SampleConsensusModelNormalParallelPlane defines a model for 3D plane segmentation using additional surface normal constraints 
CSampleConsensusModelNormalPlane  SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface normal constraints 
CSampleConsensusModelNormalSphere  SampleConsensusModelNormalSphere defines a model for 3D sphere segmentation using additional surface normal constraints 
CSampleConsensusModelParallelLine  SampleConsensusModelParallelLine defines a model for 3D line segmentation using additional angular constraints 
CSampleConsensusModelParallelPlane  SampleConsensusModelParallelPlane defines a model for 3D plane segmentation using additional angular constraints 
CSampleConsensusModelPerpendicularPlane  SampleConsensusModelPerpendicularPlane defines a model for 3D plane segmentation using additional angular constraints 
CSampleConsensusModelPlane  SampleConsensusModelPlane defines a model for 3D plane segmentation 
CSampleConsensusModelRegistration  SampleConsensusModelRegistration defines a model for PointToPoint registration outlier rejection 
CSampleConsensusModelRegistration2D  SampleConsensusModelRegistration2D defines a model for PointToPoint registration outlier rejection using distances between 2D pixels 
CSampleConsensusModelSphere  SampleConsensusModelSphere defines a model for 3D sphere segmentation 
CSampleConsensusModelStick  SampleConsensusModelStick defines a model for 3D stick segmentation 
CSampleConsensusPrerejective  Pose estimation and alignment class using a prerejective RANSAC routine 
CSamplingSurfaceNormal  SamplingSurfaceNormal divides the input space into grids until each grid contains a maximum of N points, and samples points randomly within each grid 
CScaledMultiChannel2DComparisonFeatureHandler  Feature utility class that handles the creation and evaluation of RGBD comparison features 
CScaledMultiChannel2DComparisonFeatureHandlerCCodeGenerator  
CScopeTime  Class to measure the time spent in a scope 
CSeededHueSegmentation  SeededHueSegmentation 
CSegmentDifferences  SegmentDifferences obtains the difference between two spatially aligned point clouds and returns the difference between them for a maximum given distance threshold 
CSetIfFieldExists  A helper functor that can set a specific value in a field if the field exists 
CShadowPoints  ShadowPoints removes the ghost points appearing on edge discontinuties 
CShapeContext1980  A point structure representing a Shape Context 
CShapeContext3DEstimation  ShapeContext3DEstimation implements the 3D shape context descriptor as described in: 
CSHOT1344  A point structure representing the generic Signature of Histograms of OrienTations (SHOT)  shape+color 
CSHOT352  A point structure representing the generic Signature of Histograms of OrienTations (SHOT)  shape only 
CSHOTColorEstimation  SHOTColorEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points, normals and colors 
CSHOTColorEstimationOMP  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 
CSHOTEstimation  SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals 
CSHOTEstimationBase  SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals 
CSHOTEstimationOMP  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 
CSHOTLocalReferenceFrameEstimation  SHOTLocalReferenceFrameEstimation estimates the Local Reference Frame used in the calculation of the (SHOT) descriptor 
CSHOTLocalReferenceFrameEstimationOMP  SHOTLocalReferenceFrameEstimation estimates the Local Reference Frame used in the calculation of the (SHOT) descriptor 
CSIFTKeypoint  SIFTKeypoint detects the Scale Invariant Feature Transform keypoints for a given point cloud dataset containing points and intensity 
CSIFTKeypointFieldSelector  
CSIFTKeypointFieldSelector< PointNormal >  
CSIFTKeypointFieldSelector< PointXYZRGB >  
CSIFTKeypointFieldSelector< PointXYZRGBA >  
CSmoothedSurfacesKeypoint  Based on the paper: Xinju Li and Igor Guskov Multiscale features for approximate alignment of pointbased surfaces Proceedings of the third Eurographics symposium on Geometry processing July 2005, Vienna, Austria 
CSolverDidntConvergeException  An exception that is thrown when the non linear solver didn't converge 
CSparseQuantizedMultiModTemplate  A multimodality template constructed from a set of quantized multimodality features 
CSpinImageEstimation  Estimates spinimage descriptors in the given input points 
CStaticRangeCoder  StaticRangeCoder compression class 
CStatisticalMultiscaleInterestRegionExtraction  Class for extracting interest regions from unstructured point clouds, based on a multi scale statistical approach 
CStatisticalOutlierRemoval  StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data 
CStatisticalOutlierRemoval< pcl::PCLPointCloud2 >  StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data 
CStatsEstimator  Class interface for gathering statistics for decision tree learning 
CStereoGrabber  
CStereoGrabberBase  Base class for Stereo file grabber 
CStereoMatching  Stereo Matching abstract class 
CStopWatch  Simple stopwatch 
CSupervoxel  Supervoxel container class  stores a cluster extracted using supervoxel clustering 
►CSupervoxelClustering  Implements a supervoxel algorithm based on voxel structure, normals, and rgb values 
CVoxelData  VoxelData is a structure used for storing data within a pcl::octree::OctreePointCloudAdjacencyContainer 
►CSurfaceNormalModality  Modality based on surface normals 
CCandidate  Candidate for a feature (used in feature extraction methods) 
CSurfaceReconstruction  SurfaceReconstruction represents a base surface reconstruction class 
CSurfelSmoothing  
CSUSANKeypoint  SUSANKeypoint implements a RGBD extension of the SUSAN detector including normal directions variation in top of intensity variation 
CSVM  Base class for SVM SVM (Support Vector Machines) 
CSVMClassify  SVM (Support Vector Machines) classification of a dataset 
CSVMData  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) 
CSVMDataPoint  The structure initialize a single feature value for the classification using SVM (Support Vector Machines) 
CSVMModel  The structure initialize a model created by the SVM (Support Vector Machines) classifier (pcl::SVMTrain) 
CSVMParam  The structure stores the parameters for the classificationa nd must be initialized and passed to the training method pcl::SVMTrain 
CSVMTrain  SVM (Support Vector Machines) training class for the SVM machine learning 
CSynchronizedQueue  
CSynchronizer  /brief This template class synchronizes two data streams of different types 
CTernaryTreeMissingDataBranchEstimator  Branch estimator for ternary trees where one branch is used for missing data (indicated by flag != 0) 
►CTexMaterial  
CRGB  
CTextureMapping  The texture mapping algorithm 
CTextureMesh  
CTfQuadraticXYZComparison  A comparison whether the (x,y,z) components of a given point satisfy (p'Ap + 2v'p + c [OP] 0) 
CTimeTrigger  Timer class that invokes registered callback methods periodically 
CTrajkovicKeypoint2D  TrajkovicKeypoint2D implements Trajkovic and Hedley corner detector on organized pooint cloud using intensity information 
CTrajkovicKeypoint3D  TrajkovicKeypoint3D implements Trajkovic and Hedley corner detector on point cloud using geometric information 
CTransformationFromCorrespondences  Calculates a transformation based on corresponding 3D points 
►CTSDFVolume  
CHeader  Structure storing voxel grid resolution, volume size (in mm) and element_size of stored data 
CIntr  Camera intrinsics structure 
CUnaryClassifier  
CUnhandledPointTypeException  
►CUniformSampling  UniformSampling assembles a local 3D grid over a given PointCloud, and downsamples + filters the data 
CLeaf  Simple structure to hold an nD centroid and the number of points in a leaf 
CUniqueShapeContext  UniqueShapeContext implements the Unique Shape Context Descriptor described here: 
CUniqueShapeContext1960  A point structure representing a Unique Shape Context 
CUnorganizedPointCloudException  An exception that is thrown when an organized point cloud is needed but not provided 
CVectorAverage  Calculates the weighted average and the covariance matrix 
CVertices  Describes a set of vertices in a polygon mesh, by basically storing an array of indices 
CVFHEstimation  VFHEstimation estimates the Viewpoint Feature Histogram (VFH) descriptor for a given point cloud dataset containing points and normals 
CVFHSignature308  A point structure representing the Viewpoint Feature Histogram (VFH) 
CVLPGrabber  Grabber for the Velodyne LiDAR (VLP), based on the Velodyne High Definition Laser (HDL) 
CVoxelGrid  VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data 
CVoxelGrid< pcl::PCLPointCloud2 >  VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data 
►CVoxelGridCovariance  A searchable voxel strucure containing the mean and covariance of the data 
CLeaf  Simple structure to hold a centroid, covarince and the number of points in a leaf 
CVoxelGridLabel  
CVoxelGridOcclusionEstimation  VoxelGrid to estimate occluded space in the scene 
CVTKUtils  
CxNdCopyEigenPointFunctor  Helper functor structure for copying data between an Eigen::VectorXf and a PointT 
CxNdCopyPointEigenFunctor  Helper functor structure for copying data between an Eigen::VectorXf and a PointT 
►Npcl_cuda  
CFilter  Removes points with x, y, or z equal to NaN 
CisFiniteAOS  Check if a specific point is valid or not 
CisFiniteSOA  Check if a specific point is valid or not 
CisFiniteZIPSOA  Check if a specific point is valid or not 
CMEstimatorSampleConsensus  
CPassThrough  PassThrough uses the base Filter class methods to pass through all data that satisfies the user given constraints 
CPassThrough< PointCloudAOS< Device > >  
CPassThrough< PointCloudSOA< Device > >  
CVoxelGrid  VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data 
CVoxelGrid< PointCloudAOS< Device > >  
CVoxelGrid< PointCloudSOA< Device > >  
C__pixAdd_CN  
C__pixAdd_CN< Tin, Tout, 1 >  
C__pixAdd_CN< Tin, Tout, 3 >  
C__pixAdd_CN< Tin, Tout, 4 >  
C__pixColorConv  
C__pixColorConv< NCVColorSpaceGray, NCVColorSpaceRGBA, Tin, Tout >  
C__pixColorConv< NCVColorSpaceRGBA, NCVColorSpaceGray, Tin, Tout >  
C__pixDemoteClampNN_CN  
C__pixDemoteClampNN_CN< Tin, Tout, 1 >  
C__pixDemoteClampNN_CN< Tin, Tout, 3 >  
C__pixDemoteClampNN_CN< Tin, Tout, 4 >  
C__pixDemoteClampZ_CN  
C__pixDemoteClampZ_CN< Tin, Tout, 1 >  
C__pixDemoteClampZ_CN< Tin, Tout, 3 >  
C__pixDemoteClampZ_CN< Tin, Tout, 4 >  
C__pixDist_CN  
C__pixDist_CN< Tin, Tout, 1 >  
C__pixDist_CN< Tin, Tout, 3 >  
C__pixDist_CN< Tin, Tout, 4 >  
C__pixScale_CN  
C__pixScale_CN< Tin, Tout, Tw, 1 >  
C__pixScale_CN< Tin, Tout, Tw, 3 >  
C__pixScale_CN< Tin, Tout, Tw, 4 >  
CAbstractMetadata  Abstract interface for outofcore metadata file types 
CAxes  
►CBFGS  BFGS stands for Broydenâ€“Fletcherâ€“Goldfarbâ€“Shanno (BFGS) method for solving unconstrained nonlinear optimization problems 
CParameters  
CBFGSDummyFunctor  
Cbuffer_traits  
Cbuffer_traits< double >  
Cbuffer_traits< float >  
CCamera  
CCameraPoseProcessor  Interface to extract camera pose data generated by the pcl_kinfu_app program 
CCameraPoseWriter  CameraPoseWriter writes all camera poses computed by the KinfuTracker to a file on disk 
CcJSON  
CcJSON_Hooks  
Ccloud_point_index_idx  
Ccode  
Cct_data_s  
►CDataGenerator  
CConvPoint  
CDeprecatedType  A dummy type to aid in template parameter deprecation 
CEvaluation  Class for RGBD SLAM Dataset and Benchmark 
CfunctorAddValues  
CfunctorMaxValues  
CfunctorMinValues  
CGeometry  
CGrid  
Cgz_header_s  
CHaarClassifierCascadeDescriptor  Classifier cascade descriptor 
CHaarClassifierNode128  
CHaarClassifierNodeDescriptor32  
CHaarFeature64  
CHaarFeatureDescriptor32  
CHaarStage64  
CINCVMemAllocator  INCVMemAllocator (Interface) 
Cinflate_state  
Cinternal_state  
Ckiss_fft_cpx  
Ckiss_fft_state  
CLRUCache  
CLRUCacheItem  
CMesh  
CMonitorQueue  
CNCVMatrix  NCVMatrix (2D) 
CNCVMatrixAlloc  NCVMatrixAlloc 
CNCVMatrixReuse  NCVMatrixReuse 
CNCVMemNativeAllocator  NCVMemNativeAllocator 
CNCVMemPtr  NCVMemPtr 
CNCVMemSegment  NCVMemSegment 
CNCVMemStackAllocator  NCVMemStackAllocator 
CNcvPoint2D32s  
CNcvPoint2D32u  
CNcvRect32s  
CNcvRect32u  
CNcvRect8u  
CNcvSize32s  
CNcvSize32u  
CNCVVector  NCVVector (1D) 
CNCVVectorAlloc  NCVVectorAlloc 
CNCVVectorReuse  NCVVectorReuse 
CNppStInterpolationState  Frame interpolation state 
CObject  
CObjectFeatures  
CObjectModel  
CObjectRecognition  
CObjectRecognitionParameters  
CON_2dexMap  
CON_2dPoint  
CON_2dPointArray  
CON_2dVector  
CON_2dVectorArray  
CON_2fPoint  
CON_2fPointArray  
CON_2fVector  
CON_2fVectorArray  
CON_3DM_BIG_CHUNK  
CON_3DM_CHUNK  
CON_3dmAnnotationSettings  
CON_3dmApplication  
CON_3dmConstructionPlane  
CON_3dmConstructionPlaneGridDefaults  
CON_3dmGoo  
CON_3dmIOSettings  
CON_3dmNotes  
CON_3dmObjectAttributes  
CON_3dmPageSettings  
CON_3dmProperties  
CON_3dmRenderSettings  
CON_3dmRevisionHistory  
CON_3dmSettings  
CON_3dmUnitsAndTolerances  
CON_3dmView  
CON_3dmViewPosition  
CON_3dmViewTraceImage  
CON_3dmWallpaperImage  
CON_3dPoint  
CON_3dPointArray  
CON_3dRay  
CON_3dVector  
CON_3dVectorArray  
CON_3fPoint  
CON_3fPointArray  
CON_3fVector  
CON_3fVectorArray  
CON_4dPoint  
CON_4dPointArray  
CON_4fPoint  
CON_4fPointArray  
CON_AngularDimension  
CON_AngularDimension2  
CON_Annotation  
CON_Annotation2  
CON_Annotation2Text  
CON_AnnotationArrow  
CON_AnnotationTextDot  
CON_Arc  
CON_ArcCurve  
CON_Base64EncodeStream  
CON_BezierCage  
CON_BezierCageMorph  
CON_BezierCurve  
CON_BezierSurface  
CON_BinaryArchive  
CON_BinaryArchiveBuffer  
CON_BinaryFile  
CON_Bitmap  
CON_BoundingBox  
CON_Box  
CON_Brep  
CON_BrepEdge  
CON_BrepEdgeArray  
CON_BrepFace  
CON_BrepFaceArray  
CON_BrepFaceSide  
CON_BrepFaceSideArray  
CON_BrepLoop  
CON_BrepLoopArray  
CON_BrepRegion  
CON_BrepRegionArray  
CON_BrepRegionTopology  
CON_BrepTrim  
CON_BrepTrimArray  
CON_BrepTrimPoint  
CON_BrepVertex  
CON_BrepVertexArray  
CON_Buffer  
CON_BumpFunction  
CON_CageMorph  
CON_CheckSum  
CON_Circle  
CON_ClassArray  
CON_ClassId  
CON_ClippingPlane  
CON_ClippingPlaneInfo  
CON_ClippingPlaneSurface  
CON_ClippingRegion  
CON_Color  
CON_CompressedBuffer  
CON_CompressStream  
CON_Cone  
CON_Curve  
CON_CurveArray  
CON_CurveOnSurface  
CON_CurveProxy  
CON_CurveProxyHistory  
CON_Cylinder  
CON_DecodeBase64  
CON_DetailView  
CON_DimensionExtra  
CON_DimStyle  
CON_DisplayMaterialRef  
CON_DocumentUserStringList  
CON_EarthAnchorPoint  
CON_Ellipse  
CON_EmbeddedBitmap  
CON_EmbeddedFile  
CON_Evaluator  
CON_Extrusion  
CON_FileIterator  
CON_FileStream  
CON_FixedSizePool  
CON_FixedSizePoolIterator  
CON_Font  
CON_Geometry  
CON_Group  
CON_Hatch  
CON_HatchLine  
CON_HatchLoop  
CON_HatchPattern  
CON_HistoryRecord  
CON_InstanceDefinition  
CON_InstanceRef  
CON_Interval  
CON_Layer  
CON_Leader  
CON_Leader2  
CON_Light  
CON_Line  
CON_LinearDimension  
CON_LinearDimension2  
CON_LineCurve  
CON_Linetype  
CON_LinetypeSegment  
CON_Localizer  
CON_LocalZero1  
CON_MappingChannel  
CON_MappingRef  
CON_MappingTag  
CON_Material  
CON_MaterialRef  
CON_Matrix  
CON_Mesh  
CON_MeshCurvatureStats  
CON_MeshCurveParameters  
CON_MeshEdgeRef  
CON_MeshFace  
CON_MeshFaceRef  
CON_MeshFaceSide  
CON_MeshNgon  
CON_MeshNgonList  
CON_MeshParameters  
CON_MeshPart  
CON_MeshPartition  
CON_MeshTopology  
CON_MeshTopologyEdge  
CON_MeshTopologyFace  
CON_MeshTopologyVertex  
CON_MeshVertexRef  
CON_MorphControl  
CON_NurbsCage  
CON_NurbsCurve  
CON_NurbsSurface  
CON_Object  
CON_ObjectArray  
CON_ObjectRenderingAttributes  
CON_ObjRef  
CON_ObjRef_IRefID  
CON_ObjRefEvaluationParameter  
CON_OffsetSurface  
CON_OffsetSurfaceFunction  
CON_OffsetSurfaceValue  
CON_OrdinateDimension2  
CON_Plane  
CON_PlaneEquation  
CON_PlaneSurface  
CON_PlugInRef  
CON_Point  
CON_PointCloud  
CON_PointGrid  
CON_PolyCurve  
CON_PolyEdgeCurve  
CON_PolyEdgeHistory  
CON_PolyEdgeSegment  
CON_Polyline  
CON_PolylineCurve  
CON_PolynomialCurve  
CON_PolynomialSurface  
CON_RadialDimension  
CON_RadialDimension2  
CON_RANDOM_NUMBER_CONTEXT  
CON_Read3dmBufferArchive  
CON_RenderingAttributes  
CON_RevSurface  
CON_RTree  
CON_RTreeBBox  
CON_RTreeBranch  
CON_RTreeCapsule  
CON_RTreeIterator  
CON_RTreeLeaf  
CON_RTreeMemPool  
CON_RTreeNode  
CON_RTreeSearchResult  
CON_RTreeSphere  
►CON_SerialNumberMap  
CMAP_VALUE  
CSN_ELEMENT  
CON_SimpleArray  
CON_SimpleFixedSizePool  
CON_SpaceMorph  
CON_Sphere  
CON_String  
CON_Sum  
CON_SumSurface  
CON_Surface  
CON_SurfaceArray  
CON_SurfaceCurvature  
CON_SurfaceProperties  
CON_SurfaceProxy  
CON_TensorProduct  
CON_TextDot  
CON_TextEntity  
CON_TextEntity2  
CON_TextExtra  
CON_TextLog  
CON_Texture  
CON_TextureCoordinates  
CON_TextureMapping  
CON_Torus  
CON_U  
CON_UncompressStream  
CON_UnicodeErrorParameters  
CON_UnitSystem  
CON_UnknownUserData  
CON_UserData  
CON_UserDataHolder  
CON_UserString  
CON_UserStringList  
CON_UUID  
CON_UuidIndexList  
CON_UuidList  
CON_UuidPair  
CON_UuidPairList  
CON_Viewport  
CON_WindowsBitmap  
CON_WindowsBitmapEx  
CON_WindowsBITMAPINFO  
CON_WindowsBITMAPINFOHEADER  
CON_WindowsRGBQUAD  
CON_Workspace  
CON_Write3dmBufferArchive  
CON_wString  
CON_Xform  
CONX_Model  
CONX_Model_Object  
CONX_Model_RenderLight  
CONX_Model_UserData  
COpenNICapture  
►COutofcoreCloud  
CCloudDataCacheItem  
CPcdQueueItem  
CPCLViewer  
Cpoint_index_idx  
CPointIntensity  
CScene  
Csvm_model  
Csvm_node  
Csvm_parameter  
Csvm_problem  
Csvm_scaling  
CTAccPixDist  
CTAccPixDist< float1 >  
CTAccPixDist< float3 >  
CTAccPixDist< float4 >  
CTAccPixDist< uchar1 >  
CTAccPixDist< uchar3 >  
CTAccPixDist< uchar4 >  
CTAccPixDist< ushort1 >  
CTAccPixDist< ushort3 >  
CTAccPixDist< ushort4 >  
CTAccPixWeighted  
CTAccPixWeighted< float1 >  
CTAccPixWeighted< float3 >  
CTAccPixWeighted< float4 >  
CTAccPixWeighted< uchar1 >  
CTAccPixWeighted< uchar3 >  
CTAccPixWeighted< uchar4 >  
CTAccPixWeighted< ushort1 >  
CTAccPixWeighted< ushort3 >  
CTAccPixWeighted< ushort4 >  
CtagON_2dex  
CtagON_3dex  
CtagON_4dex  
CtagON_RECT  
CTConvBase2Vec  
CTConvBase2Vec< Ncv16u, 1 >  
CTConvBase2Vec< Ncv16u, 3 >  
CTConvBase2Vec< Ncv16u, 4 >  
CTConvBase2Vec< Ncv32f, 1 >  
CTConvBase2Vec< Ncv32f, 3 >  
CTConvBase2Vec< Ncv32f, 4 >  
CTConvBase2Vec< Ncv32u, 1 >  
CTConvBase2Vec< Ncv32u, 3 >  
CTConvBase2Vec< Ncv32u, 4 >  
CTConvBase2Vec< Ncv64f, 1 >  
CTConvBase2Vec< Ncv64f, 3 >  
CTConvBase2Vec< Ncv64f, 4 >  
CTConvBase2Vec< Ncv8u, 1 >  
CTConvBase2Vec< Ncv8u, 3 >  
CTConvBase2Vec< Ncv8u, 4 >  
CTConvVec2Base  
CTConvVec2Base< double1 >  
CTConvVec2Base< double3 >  
CTConvVec2Base< double4 >  
CTConvVec2Base< float1 >  
CTConvVec2Base< float3 >  
CTConvVec2Base< float4 >  
CTConvVec2Base< uchar1 >  
CTConvVec2Base< uchar3 >  
CTConvVec2Base< uchar4 >  
CTConvVec2Base< uint1 >  
CTConvVec2Base< uint3 >  
CTConvVec2Base< uint4 >  
CTConvVec2Base< ushort1 >  
CTConvVec2Base< ushort3 >  
CTConvVec2Base< ushort4 >  
Ctree_desc_s  
CViewport  
CvtkSmartPointer  
CvtkVertexBufferObject  
CvtkVertexBufferObjectMapper  
Cz_stream_s 
Except where otherwise noted, the PointClouds.org web pages are licensed under Creative Commons Attribution 3.0.
Pages generated on Wed Apr 24 2019 10:29:33