small_gicp
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▼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 |