CPonca::KdTreeBase< Traits >::DefaultConverter | Convert a custom point container to the KdTree PointContainer using DataPoint default constructor |
CPonca::DistWeightFunc< DataPoint, WeightKernel > | Weighting function based on the euclidean distance between a query and a reference position |
CPonca::QueryOutputBase::DummyOutputParameter | |
►CConcept::FittingExtensionConcept | |
CPonca::CovarianceFitDer< DataPoint, _WFunctor, DiffType, T > | Internal generic class computing the derivatives of covariance matrix computed by CovarianceFitBase |
CPonca::CovariancePlaneDerImpl< DataPoint, _WFunctor, DiffType, T > | [CovariancePlaneFit Definition] |
CPonca::GLSDer< DataPoint, _WFunctor, DiffType, T > | Differentiation of GLSParam |
CPonca::GLSParam< DataPoint, _WFunctor, T > | Growing Least Squares reparemetrization of the OrientedSphereFit |
CPonca::MlsSphereFitDer< DataPoint, _WFunctor, DiffType, T > | Extension performing derivation of the mls surface |
CPonca::NormalDerivativesCurvatureEstimator< DataPoint, _WFunctor, DiffType, T > | Extension to compute curvature values from the Weingarten map \( \frac{d N}{d \mathbf{x}} \) |
CPonca::PrimitiveDer< DataPoint, _WFunctor, Type, T > | Generic class performing the Fit derivation |
►CConcept::FittingProcedureConcept | |
CPonca::CovarianceFitBase< DataPoint, _WFunctor, T > | Procedure that compute and decompose the covariance matrix of the neighbors positions in \(3d\) |
CPonca::CovarianceLineFitImpl< DataPoint, _WFunctor, T > | Line fitting procedure that minimize the orthogonal distance between the samples and the fitted primitive |
CPonca::CovariancePlaneFitImpl< DataPoint, _WFunctor, T > | Plane fitting procedure using only points position |
CPonca::MeanNormal< DataPoint, _WFunctor, T > | Compute the barycenter of the input points + their normals |
CPonca::MeanPlaneFitImpl< DataPoint, _WFunctor, T > | Plane fitting procedure computing the mean position and orientation from oriented points |
CPonca::MeanPosition< DataPoint, _WFunctor, T > | Compute the barycenter of the input points |
CPonca::OrientedSphereFitImpl< DataPoint, _WFunctor, T > | Algebraic Sphere fitting procedure on oriented point sets |
CPonca::SphereFitImpl< DataPoint, _WFunctor, T > | Algebraic Sphere fitting procedure on point set without normals |
CPonca::UnorientedSphereFitImpl< DataPoint, _WFunctor, T > | Algebraic Sphere fitting procedure on point sets with non-oriented normals |
►CEigen::Hyperplane | |
CPonca::Plane< DataPoint, _WFunctor, T > | Implicit hyperplane defined by an homogeneous vector \(\mathbf{p}\) |
CPonca::IndexSquaredDistance< Index, Scalar > | Associates an index with a distance |
CPonca::IndexSquaredDistance< Index, DataPoint::Scalar > | |
CPonca::IndexSquaredDistance< IndexType, Scalar > | |
CPonca::IndexSquaredDistance< Traits::IndexType, Traits::DataPoint::Scalar > | |
►CInput_ | |
►CPonca::Query< Input_, Output_ > | |
►CPonca::KNearestIndexQuery< Traits::IndexType, Traits::DataPoint::Scalar > | |
CPonca::KnnGraphKNearestQuery< Traits > | |
►CPonca::RangeIndexQuery< Traits::IndexType, Traits::DataPoint::Scalar > | |
CPonca::KnnGraphRangeQuery< Traits > | |
►CPonca::KdTreeBase< Traits > | [KdTreeSparse type definition] |
►CPonca::KdTreeDenseBase< KdTreeDefaultTraits< DataPoint > > | |
CPonca::KdTreeDense< DataPoint > | [KdTree type definition] |
►CPonca::KdTreeSparseBase< KdTreeDefaultTraits< DataPoint > > | |
CPonca::KdTreeSparse< DataPoint > | [KdTreeDense type definition] |
CPonca::KdTreeDenseBase< Traits > | Customizable base class for dense KdTree datastructure |
CPonca::KdTreeSparseBase< Traits > | Customizable base class for KdTreeSparse datastructure |
►CPonca::KdTreeBase< KdTreeDefaultTraits< DataPoint > > | |
CPonca::KdTree< DataPoint > | Abstract KdTree type with KdTreeDefaultTraits |
►CPonca::KdTreeCustomizableNode< Index, NodeIndex, DataPoint, LeafSize, _InnerNodeType, _LeafNodeType > | The node type used by default by the kd-tree |
CPonca::KdTreeDefaultNode< Index, NodeIndex, DataPoint, LeafSize > | |
CPonca::KdTreeCustomizableNode< Index, NodeIndex, DataPoint, Index, KdTreeDefaultInnerNode< NodeIndex, DataPoint::Scalar, DataPoint::Dim >, KdTreeDefaultLeafNode< Index, Index > > | |
CPonca::KdTreeDefaultInnerNode< NodeIndex, Scalar, DIM > | |
CPonca::KdTreeDefaultLeafNode< Index, Size > | |
CPonca::KdTreeDefaultTraits< _DataPoint, _NodeType > | The default traits type used by the kd-tree |
CPonca::KdTreeKNearestIterator< Index, DataPoint > | |
CPonca::KdTreeNearestIterator< Index > | |
►CPonca::KdTreeQuery< Traits > | |
CPonca::KdTreeKNearestQueryBase< Traits, IteratorType, QueryType > | |
CPonca::KdTreeNearestQueryBase< Traits, IteratorType, QueryType > | |
CPonca::KdTreeRangeQueryBase< Traits, IteratorType, QueryType > | |
CPonca::KdTreeRangeIterator< Index, DataPoint, QueryT_ > | |
CPonca::KnnGraphBase< Traits > | Customizable base class for KnnGraph datastructure |
CPonca::KnnGraphDefaultTraits< _DataPoint > | The default traits type used by the kd-tree |
CPonca::KnnGraphRangeIterator< Traits > | |
CPonca::limited_priority_queue< T, CompareT > | The limited_priority_queue class is similar to std::priority_queue but has a limited capacity and handles the comparison differently |
CPonca::limited_priority_queue< IndexSquaredDistance< Index, Scalar > > | |
CPonca::limited_priority_queue< Ponca::IndexSquaredDistance< Index, DataPoint::Scalar > > | |
CPonca::limited_priority_queue< Ponca::IndexSquaredDistance< Index, Scalar > > | |
CPonca::limited_priority_queue< Ponca::IndexSquaredDistance< Traits::IndexType, Traits::DataPoint::Scalar > > | |
►COutput_ | |
CPonca::Query< Input_, Output_ > | |
►CEigen::ParametrizedLine | |
CPonca::Line< DataPoint, _WFunctor, T > | A parametrized line is defined by an origin point \(\mathbf{o}\) and a unit direction vector \(\overrightarrow{\mathbf{d}}\) such that the line corresponds to the set \(l(t)=\mathbf{o}+t\overrightarrow{\mathbf{d}}, t\in \mathbb{R}\) |
CPonca::PrimitiveBase< DataPoint, _WFunctor, T > | Primitive base class |
►CPonca::QueryInputBase | Base class for queries input type |
CPonca::QueryInput< Traits::IndexType > | |
►CPonca::QueryInput< Index > | |
►CPonca::QueryInputIsIndex< Index > | Base class for queries storing points |
►CPonca::Query< QueryInputIsIndex< Index >, QueryOutputIsKNearest< Index, Scalar > > | |
CPonca::KNearestIndexQuery< Index, Scalar > | Base Query class combining QueryInputIsIndex and QueryOutputIsKNearest |
►CPonca::Query< QueryInputIsIndex< Index >, QueryOutputIsNearest< Index, Scalar > > | |
CPonca::NearestIndexQuery< Index, Scalar > | Base Query class combining QueryInputIsIndex and QueryOutputIsNearest |
►CPonca::Query< QueryInputIsIndex< Index >, QueryOutputIsRange< Index, Scalar > > | |
CPonca::RangeIndexQuery< Index, Scalar > | Base Query class combining QueryInputIsIndex and QueryOutputIsRange |
►CPonca::QueryInput< DataPoint::VectorType > | |
►CPonca::QueryInputIsPosition< DataPoint > | Base class for queries storing points |
►CPonca::Query< QueryInputIsPosition< DataPoint >, QueryOutputIsKNearest< Index, DataPoint::Scalar > > | |
CPonca::KNearestPointQuery< Index, DataPoint > | Base Query class combining QueryInputIsPosition and QueryOutputIsKNearest |
►CPonca::Query< QueryInputIsPosition< DataPoint >, QueryOutputIsNearest< Index, DataPoint::Scalar > > | |
CPonca::NearestPointQuery< Index, DataPoint > | Base Query class combining QueryInputIsPosition and QueryOutputIsNearest |
►CPonca::Query< QueryInputIsPosition< DataPoint >, QueryOutputIsRange< Index, DataPoint::Scalar > > | |
CPonca::RangePointQuery< Index, DataPoint > | Base Query class combining QueryInputIsPosition and QueryOutputIsRange |
►CPonca::QueryInput< InputType_ > | Base class for typed queries input type |
►CPonca::QueryInputIsIndex< Traits::IndexType > | |
CPonca::Query< QueryInputIsIndex< Traits::IndexType >, QueryOutputIsKNearest< Traits::IndexType, Traits::DataPoint::Scalar > > | |
CPonca::Query< QueryInputIsIndex< Traits::IndexType >, QueryOutputIsRange< Traits::IndexType, Traits::DataPoint::Scalar > > | |
►CPonca::QueryOutputBase | Base class for queries output type |
►CPonca::QueryOutputIsKNearest< Index, DataPoint::Scalar > | |
CPonca::Query< QueryInputIsPosition< DataPoint >, QueryOutputIsKNearest< Index, DataPoint::Scalar > > | |
►CPonca::QueryOutputIsKNearest< Traits::IndexType, Traits::DataPoint::Scalar > | |
CPonca::Query< QueryInputIsIndex< Traits::IndexType >, QueryOutputIsKNearest< Traits::IndexType, Traits::DataPoint::Scalar > > | |
►CPonca::QueryOutputIsNearest< Index, DataPoint::Scalar > | |
CPonca::Query< QueryInputIsPosition< DataPoint >, QueryOutputIsNearest< Index, DataPoint::Scalar > > | |
►CPonca::QueryOutputIsRange< Traits::IndexType, Traits::DataPoint::Scalar > | |
CPonca::Query< QueryInputIsIndex< Traits::IndexType >, QueryOutputIsRange< Traits::IndexType, Traits::DataPoint::Scalar > > | |
►CPonca::QueryOutputIsRange< Index, DataPoint::Scalar > | |
CPonca::Query< QueryInputIsPosition< DataPoint >, QueryOutputIsRange< Index, DataPoint::Scalar > > | |
►CPonca::QueryOutputIsKNearest< Index, Scalar > | Base class for knearest queries |
CPonca::Query< QueryInputIsIndex< Index >, QueryOutputIsKNearest< Index, Scalar > > | |
►CPonca::QueryOutputIsNearest< Index, Scalar > | Base class for nearest queries |
CPonca::Query< QueryInputIsIndex< Index >, QueryOutputIsNearest< Index, Scalar > > | |
►CPonca::QueryOutputIsRange< Index, Scalar > | Base class for range queries |
CPonca::Query< QueryInputIsIndex< Index >, QueryOutputIsRange< Index, Scalar > > | |
►CQueryType | |
CPonca::KdTreeKNearestQueryBase< Traits, IteratorType, QueryType > | |
CPonca::KdTreeNearestQueryBase< Traits, IteratorType, QueryType > | |
CPonca::KdTreeRangeQueryBase< Traits, IteratorType, QueryType > | |
CPonca::Stack< T, N > | Stack with fixed-size storage |
CPonca::Stack< Ponca::IndexSquaredDistance< IndexType, Scalar >, 2 *Traits::MAX_DEPTH > | |
►CT | |
CPonca::AlgebraicSphere< DataPoint, _WFunctor, T > | Algebraic Sphere primitive |
CPonca::CovarianceFitBase< DataPoint, _WFunctor, T > | Procedure that compute and decompose the covariance matrix of the neighbors positions in \(3d\) |
CPonca::CovarianceFitDer< DataPoint, _WFunctor, DiffType, T > | Internal generic class computing the derivatives of covariance matrix computed by CovarianceFitBase |
CPonca::CovarianceLineFitImpl< DataPoint, _WFunctor, T > | Line fitting procedure that minimize the orthogonal distance between the samples and the fitted primitive |
CPonca::CovariancePlaneDerImpl< DataPoint, _WFunctor, DiffType, T > | [CovariancePlaneFit Definition] |
CPonca::CovariancePlaneFitImpl< DataPoint, _WFunctor, T > | Plane fitting procedure using only points position |
CPonca::CurvatureEstimatorBase< DataPoint, _WFunctor, DiffType, T > | Base class for any 3d curvature estimator: holds \(k_{\min}\), \(k_{\max}\) and associated vectors, such that \( k_{\min} <= k_{\max} \) |
CPonca::DryFit< DataPoint, _WFunctor, T > | Empty fitting object doing no computation |
CPonca::GLSDer< DataPoint, _WFunctor, DiffType, T > | Differentiation of GLSParam |
CPonca::GLSParam< DataPoint, _WFunctor, T > | Growing Least Squares reparemetrization of the OrientedSphereFit |
CPonca::Line< DataPoint, _WFunctor, T > | A parametrized line is defined by an origin point \(\mathbf{o}\) and a unit direction vector \(\overrightarrow{\mathbf{d}}\) such that the line corresponds to the set \(l(t)=\mathbf{o}+t\overrightarrow{\mathbf{d}}, t\in \mathbb{R}\) |
CPonca::MeanNormal< DataPoint, _WFunctor, T > | Compute the barycenter of the input points + their normals |
CPonca::MeanNormalDer< DataPoint, _WFunctor, DiffType, T > | |
CPonca::MeanPlaneFitImpl< DataPoint, _WFunctor, T > | Plane fitting procedure computing the mean position and orientation from oriented points |
CPonca::MeanPosition< DataPoint, _WFunctor, T > | Compute the barycenter of the input points |
CPonca::MeanPositionDer< DataPoint, _WFunctor, DiffType, T > | |
CPonca::MlsSphereFitDer< DataPoint, _WFunctor, DiffType, T > | Extension performing derivation of the mls surface |
CPonca::MongePatch< DataPoint, _WFunctor, T > | Extension to compute the best fit quadric on 3d points expressed as \(f(u,v)=h\) |
CPonca::NormalCovarianceCurvatureEstimator< DataPoint, _WFunctor, DiffType, T > | Extension to compute curvature values based on a covariance analysis of normal vectors of neighbors |
CPonca::NormalDerivativesCurvatureEstimator< DataPoint, _WFunctor, DiffType, T > | Extension to compute curvature values from the Weingarten map \( \frac{d N}{d \mathbf{x}} \) |
CPonca::OrientedSphereDerImpl< DataPoint, _WFunctor, DiffType, T > | [OrientedSphereFit Definition] |
CPonca::OrientedSphereFitImpl< DataPoint, _WFunctor, T > | Algebraic Sphere fitting procedure on oriented point sets |
CPonca::Plane< DataPoint, _WFunctor, T > | Implicit hyperplane defined by an homogeneous vector \(\mathbf{p}\) |
CPonca::PrimitiveDer< DataPoint, _WFunctor, Type, T > | Generic class performing the Fit derivation |
CPonca::ProjectedNormalCovarianceCurvatureEstimator< DataPoint, _WFunctor, DiffType, T > | Extension to compute curvature values based on a covariance analysis of normal vectors of neighbors projected onto the tangent plane |
CPonca::SphereFitImpl< DataPoint, _WFunctor, T > | Algebraic Sphere fitting procedure on point set without normals |
CPonca::UnorientedSphereDerImpl< DataPoint, _WFunctor, DiffType, T > | |
CPonca::UnorientedSphereFitImpl< DataPoint, _WFunctor, T > | Algebraic Sphere fitting procedure on point sets with non-oriented normals |
►Cinternal::BasketAggregate::type | |
CPonca::Basket< P, W, Ext0, Exts > | Aggregator class used to declare specialized structures using CRTP |
►Cinternal::BasketDiffAggregate::type | |
CPonca::BasketDiff< BasketType, Type, Ext0, Exts > | Aggregator class used to declare specialized structures with derivatives computations, using CRTP |
►CConcept::WeightKernelConcept | |
CPonca::CompactExpWeightKernel< _Scalar > | Compact Exponential WeightKernel defined in \(\left[0 : 1\right]\) |
CPonca::ConstantWeightKernel< _Scalar > | Concept::WeightKernelConcept returning a constant value |
CPonca::SingularWeightKernel< _Scalar > | Singular WeightKernel defined in \(\left]0 : 1\right]\) |
CPonca::SmoothWeightKernel< _Scalar > | Smooth WeightKernel defined in \(\left[0 : 1\right]\) |
CPonca::WendlandWeightKernel< _Scalar > | Wendland WeightKernel defined in \(\left[0 : 1\right]\) |