Classes | |
struct | DummyTransformVisitor |
Public Types | |
using | PairsVector = std::vector< std::pair< int, int > > |
using | Scalar = typename Point3D::Scalar |
using | VectorType = typename Point3D::VectorType |
using | MatrixType = Eigen::Matrix< Scalar, 4, 4 > |
using | LogLevel = Utils::LogLevel |
using | DefaultSampler = Sampling::UniformDistSampler |
Public Member Functions | |
virtual EIGEN_MAKE_ALIGNED_OPERATOR_NEW | ~Match4PCSBase () |
const std::vector< Point3D > & | getFirstSampled () const |
Read access to the sampled clouds used for the registration. More... | |
const std::vector< Point3D > & | getSecondSampled () const |
Read access to the sampled clouds used for the registration. More... | |
template<typename Sampler = DefaultSampler, typename Visitor = DummyTransformVisitor> | |
Scalar | ComputeTransformation (const std::vector< Point3D > &P, std::vector< Point3D > *Q, Eigen::Ref< MatrixType > transformation, const Sampler &sampler=Sampler(), const Visitor &v=Visitor()) |
Computes an approximation of the best LCP (directional) from Q to P and the rigid transformation that realizes it. The input sets may or may not contain normal information for any point. More... | |
Static Public Attributes | |
static constexpr int | kNumberOfDiameterTrials = 1000 |
static constexpr Scalar | kLargeNumber = 1e9 |
static constexpr Scalar | distance_factor = 2.0 |
using GlobalRegistration::Match4PCSBase::MatrixType = Eigen::Matrix<Scalar, 4, 4> |
using GlobalRegistration::Match4PCSBase::PairsVector = std::vector< std::pair<int, int> > |
using GlobalRegistration::Match4PCSBase::Scalar = typename Point3D::Scalar |
using GlobalRegistration::Match4PCSBase::VectorType = typename Point3D::VectorType |
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virtual |
Match4PCSBase::Scalar GlobalRegistration::Match4PCSBase::ComputeTransformation | ( | const std::vector< Point3D > & | P, |
std::vector< Point3D > * | Q, | ||
Eigen::Ref< MatrixType > | transformation, | ||
const Sampler & | sampler = Sampler() , |
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const Visitor & | v = Visitor() |
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Computes an approximation of the best LCP (directional) from Q to P and the rigid transformation that realizes it. The input sets may or may not contain normal information for any point.
[in] | P | The first input set. |
[in] | Q | The second input set. as a fraction of the size of P ([0..1]). |
[out] | transformation | Rigid transformation matrix (4x4) that brings Q to the (approximate) optimal LCP. Initial value is considered as a guess |
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inline |
Read access to the sampled clouds used for the registration.
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Read access to the sampled clouds used for the registration.
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