Go to the documentation of this file.
56 return "Subsampling. This filter reduces the size of the point cloud by randomly dropping points. Based on \\cite{Masuda1996Random}";
61 {
"prob",
"Probability to keep a point, one over decimation factor ",
"0.75",
"0",
"1", &P::Comp<T>},
62 {
"randomSamplingMethod",
"Random sampling method: Direct RNG (0) (fastest), Uniform (1) (more accurate but slower)",
"0",
"0",
"1", &P::Comp<int>},
63 {
"seed",
"Seed for random sampling (-1 means no seed is used)",
"-1",
"-1",
"2147483647", &P::Comp<int>}
PM::DataPointsFilter DataPointsFilter
PointMatcherSupport::Parametrizable P
Functions and classes that are dependant on scalar type are defined in this templatized class.
virtual void inPlaceFilter(DataPoints &cloud)
Apply these filters to a point cloud without copying.
virtual DataPoints filter(const DataPoints &input)
Apply filters to input point cloud. This is the non-destructive version and returns a copy.
static const ParametersDoc availableParameters()
const int randomSamplingMethod
Parametrizable::ParameterDoc ParameterDoc
Parametrizable::ParametersDoc ParametersDoc
std::vector< ParameterDoc > ParametersDoc
The documentation of all parameters.
Parametrizable::InvalidParameter InvalidParameter
static const std::string description()
Parametrizable::Parameters Parameters
Eigen::VectorXf sampleRandomIndices(const size_t nbPoints)
An exception thrown when one tries to fetch the value of an unexisting parameter.
PointMatcherSupport::Parametrizable Parametrizable
The superclass of classes that are constructed using generic parameters. This class provides the para...
virtual ~RandomSamplingDataPointsFilter()
The documentation of a parameter.
PointMatcher< T >::DataPoints DataPoints
RandomSamplingDataPointsFilter(const Parameters ¶ms=Parameters())
std::map< std::string, Parameter > Parameters
Parameters stored as a map of string->string.