Public Member Functions | |
std::size_t | getJacSize () |
Get degree of freedom of Jac matrix. | |
std::size_t | getMeasDim () |
Get size/length of a single feature element. | |
bool | getUseMHypos () |
Return true, if this measurement contains multi-hypotheses data structures for z and E. | |
void | resizeAll (std::size_t measDim_, std::size_t jacSize_, std::vector< std::size_t > *multiHypos=NULL) |
Resizes all vectors within structure and sets internal variables accordingly. | |
T_MEAS_OBJ (std::size_t measDim_=0, std::size_t jacSize_=0, std::vector< std::size_t > *multiHypos=NULL) | |
Public Attributes | |
std::vector< std::vector < double > > | E_mHypo |
E = pose residuals (z-h). | |
std::vector< double > | E_sHypo |
std::vector< double > | h |
h = predicted pose (= initial value) | |
std::vector< double > | invCov |
invCov = covariance of pose parameters (= uncertainty of optimization procedure) | |
std::vector< std::vector < double > > | Jac |
Jac = I or [I | 0]. | |
std::vector< std::vector < double > > | z_mHypo |
z = optimized pose | |
std::vector< double > | z_sHypo |
opentl::core::cvdata::T_MEAS_OBJ::T_MEAS_OBJ | ( | std::size_t | measDim_ = 0 , |
|
std::size_t | jacSize_ = 0 , |
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std::vector< std::size_t > * | multiHypos = NULL | |||
) | [inline] |
std::size_t opentl::core::cvdata::T_MEAS_OBJ::getJacSize | ( | ) | [inline] |
Get degree of freedom of Jac matrix.
std::size_t opentl::core::cvdata::T_MEAS_OBJ::getMeasDim | ( | ) | [inline] |
Get size/length of a single feature element.
bool opentl::core::cvdata::T_MEAS_OBJ::getUseMHypos | ( | ) | [inline] |
Return true, if this measurement contains multi-hypotheses data structures for z and E.
void opentl::core::cvdata::T_MEAS_OBJ::resizeAll | ( | std::size_t | measDim_, | |
std::size_t | jacSize_, | |||
std::vector< std::size_t > * | multiHypos = NULL | |||
) | [inline] |
Resizes all vectors within structure and sets internal variables accordingly.
nMeas_ | Number of features. | |
featElementDim_ | Length of one feature element. | |
jacSize_ | 1st dim of matrix Jac |
std::vector<std::vector<double> > opentl::core::cvdata::T_MEAS_OBJ::E_mHypo |
E = pose residuals (z-h).
std::vector<double> opentl::core::cvdata::T_MEAS_OBJ::E_sHypo |
std::vector<double> opentl::core::cvdata::T_MEAS_OBJ::h |
h = predicted pose (= initial value)
std::vector<double> opentl::core::cvdata::T_MEAS_OBJ::invCov |
invCov = covariance of pose parameters (= uncertainty of optimization procedure)
std::vector<std::vector<double> > opentl::core::cvdata::T_MEAS_OBJ::Jac |
Jac = I or [I | 0].
std::vector<std::vector<double> > opentl::core::cvdata::T_MEAS_OBJ::z_mHypo |
z = optimized pose
std::vector<double> opentl::core::cvdata::T_MEAS_OBJ::z_sHypo |