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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 |
1.9.1