Namespace List

Here is a list of all namespaces with brief descriptions:

[detail level 123]

▼Npcl
CPointCovariance	Point with covariance for PCL
CPointNormalCovariance	Point with normal and covariance for PCL
▼Nsmall_gicp
▼Ntraits
CTraits< FlatContainer< HasNormals, HasCovs > >
CTraits< GaussianVoxel >
CTraits< IncrementalVoxelMap< VoxelContents > >
CTraits< UnsafeKdTree< PointCloud, Projection > >
CTraits< KdTree< PointCloud, Projection > >
CTraits
Chas_nearest_neighbor_search	Check if T has nearest_neighbor_search method
CTraits< pcl::PointCloud< PointType > >
CTraits< PointCloudProxy< PointT > >
CTraits< Eigen::MatrixXd >
CTraits< PointCloud >
▼CFlatContainer	Point container with a flat vector
CEmpty
CSetting	FlatContainer setting
▼CGaussianVoxel	Gaussian voxel that computes and stores voxel mean and covariance
CSetting
CVoxelInfo	Voxel meta information
CIncrementalVoxelMap	Incremental voxelmap. This class supports incremental point cloud insertion and LRU-based voxel deletion that removes voxels that are not recently referenced
CKdTreeNode	KdTree node
CKdTreeBuilder	Single thread Kd-tree builder
CUnsafeKdTree	"Unsafe" KdTree
CKdTree	"Safe" KdTree that holds the ownership of the input points
CKdTreeBuilderOMP	Kd-tree builder with OpenMP
CKdTreeBuilderTBB	Kd-tree builder with TBB
CKnnSetting	K-nearest neighbor search setting
Cidentity_transform	Identity transform (alternative to std::identity in C++20)
CKnnResult	K-nearest neighbor search result container
CProjectionSetting	Parameters to control the projection axis search
CAxisAlignedProjection	Conventional axis-aligned projection (i.e., selecting any of XYZ axes with the largest variance)
CNormalProjection	Normal projection (i.e., selecting the 3D direction with the largest variance of the points)
CNullFactor	Null factor that gives no constraints
CRestrictDoFFactor	Factor to restrict the degrees of freedom of optimization (e.g., fixing roll, pitch rotation)
▼CGICPFactor	GICP (distribution-to-distribution) per-point error factor
CSetting
▼CICPFactor	Point-to-point per-point error factor
CSetting
▼CPointToPlaneICPFactor	Point-to-plane per-point error factor
CSetting
▼CHuber	Huber robust kernel
CSetting	Huber robust kernel setting
▼CCauchy	Cauchy robust kernel
CSetting	Huber robust kernel setting
▼CRobustFactor	Robustify a factor with a robust kernel
CSetting	Robust factor setting
CPointCloudProxy	Proxy class to access PCL point cloud with external covariance matrices
CRegistrationPCL	PCL registration interfaces
CPointCloud	Point cloud
CGaussNewtonOptimizer	GaussNewton optimizer
CLevenbergMarquardtOptimizer	LevenbergMarquardt optimizer
CSerialReduction	Single-thread reduction
CParallelReductionOMP	Parallel reduction with OpenMP backend
CLinearizeSum	Summation for linearized systems
CErrorSum	Summation for evaluated errors
CParallelReductionTBB	Parallel reduction with TBB backend
CRegistration	Point cloud registration
CRegistrationSetting	Registration setting
CRegistrationResult	Registration result
CNullRejector	Null correspondence rejector. This class accepts all input correspondences
CDistanceRejector	Rejecting correspondences with large distances
CTerminationCriteria	Registration termination criteria
CNormalSetter	Computes point normals from eigenvectors and sets them to the point cloud
CCovarianceSetter	Computes point covariances from eigenvectors and sets them to the point cloud
CNormalCovarianceSetter	Computes point normals and covariances from eigenvectors and sets them to the point cloud
CRadixSortBuffers	Temporal buffers for radix sort
CXORVector3iHash	Spatial hashing function. Teschner et al., "Optimized Spatial Hashing for Collision Detection of Deformable Objects", VMV2003