Class List
Here are the classes, structs, unions and interfaces with brief descriptions:
[detail level 1234]
 NPointMatcherSupportFunctions and classes that are not dependant on scalar type are defined in this namespace
 Npython
 Nsetup
 Nstd
 Ntesting
 CAddDescriptorDataPointsFilterAdd new descriptor to an existing point cloud
 CBoundingBoxDataPointsFilterSubsampling. Remove point laying in a bounding box
 CConfig
 CCovarianceSamplingDataPointsFilter
 CCutAtDescriptorThresholdDataPointsFilterSubsampling. Cut points with value of a given descriptor above or below a given threshold
 CDataFilterTest
 CDataPointsFiltersImpl
 CDataSetInfo
 CDistanceLimitDataPointsFilterSubsampling. Filter points based on distance measured on a specific axis
 CElipsoidsDataPointsFilterSubsampling Surfels (Elipsoids) filter. First decimate the space until there is at most knn points, then find the center of mass and use the points to estimate nromal using eigen-decomposition
 CErrorMinimizersImpl
 CErrorMinimizerTest
 CEvaluationModule
 CFixStepSamplingDataPointsFilterSystematic sampling, with variation over time
 CGenericTest
 CGestaltDataPointsFilterGestalt descriptors filter as described in Bosse & Zlot ICRA 2013
 ChTensor Voting framework for inference of structures
 ChOctree class for DataPoints spatial representation
 CIcpHelper
 CIdentityDataPointsFilterIdentityDataPointsFilter, does nothing
 CIdentityErrorMinimizer
 CIncidenceAngleDataPointsFilterIncidence angle, compute the incidence angle of a surface normal with the observation direction
 CInspectorsImpl
 CIOLoadSaveTest
 CLAUPointMatcherWidget
 CMatchersImpl
 CMatcherTest
 CMaxDensityDataPointsFilterSubsampling. Reduce the points number by randomly removing points with a dentsity higher than a treshold
 CMaxDistDataPointsFilterSubsampling. Filter points beyond a maximum distance measured on a specific axis
 CMaxPointCountDataPointsFilterMaximum number of points
 CMaxQuantileOnAxisDataPointsFilterSubsampling. Filter points beyond a maximum quantile measured on a specific axis
 CMinDistDataPointsFilterSubsampling. Filter points before a minimum distance measured on a specific axis
 CNormalSpaceDataPointsFilter
 CObservationDirectionDataPointsFilterExtract observation direction
 COctree_
 COctreeGridDataPointsFilterData Filter based on Octree representation
 COctreeHelper
 COctreeHelper< T, 2 >
 COctreeHelper< T, 3 >
 COrientNormalsDataPointsFilterReorientation of normals
 COutlierFiltersImpl
 COutlierFilterTest
 CPointCloudGeneratorTest
 CPointMatcherFunctions and classes that are dependant on scalar type are defined in this templatized class
 CPointMatcherIOIO Functions and classes that are dependant on scalar type are defined in this templatized class
 CPointToPlaneErrorMinimizer
 CPointToPlaneWithCovErrorMinimizer
 CPointToPointErrorMinimizer
 CPointToPointSimilarityErrorMinimizer
 CPointToPointWithCovErrorMinimizer
 CRandomSamplingDataPointsFilterRandom sampling
 CRemoveNaNDataPointsFilterRemove points having NaN as coordinate
 CRemoveSensorBiasDataPointsFilter
 CSaliencyDataPointsFilter
 CSamplingSurfaceNormalDataPointsFilterSampling surface normals. First decimate the space until there is at most knn points, then find the center of mass and use the points to estimate nromal using eigen-decomposition
 CShadowDataPointsFilterShadow filter, remove ghost points appearing on edges
 CSimpleSensorNoiseDataPointsFilterSick LMS-xxx noise model
 CSpectralDecompositionDataPointsFilter
 CSphericalityDataPointsFilter
 CSurfaceNormalDataPointsFilterSurface normals estimation. Find the normal for every point using eigen-decomposition of neighbour points
 CTensorVoting
 CTransformationCheckersImpl
 CTransformationCheckerTest
 CTransformationsImpl
 CVoxelGridDataPointsFilter


libpointmatcher
Author(s):
autogenerated on Mon Sep 16 2024 02:24:12