pcl::distances Namespace Reference

Functions
double	computeMedian (double *fvec, int m)
	Compute the median value from a set of doubles. More...
double	huber (const Eigen::Vector4f &p_src, const Eigen::Vector4f &p_tgt, double sigma)
	Use a Huber kernel to estimate the distance between two vectors. More...
double	huber (double diff, double sigma)
	Use a Huber kernel to estimate the distance between two vectors. More...
double	gedikli (double val, double clipping, double slope=4)
	Use a Gedikli kernel to estimate the distance between two vectors (for more information, see. More...
double	l1 (const Eigen::Vector4f &p_src, const Eigen::Vector4f &p_tgt)
	Compute the Manhattan distance between two eigen vectors. More...
double	l2 (const Eigen::Vector4f &p_src, const Eigen::Vector4f &p_tgt)
	Compute the Euclidean distance between two eigen vectors. More...
double	l2Sqr (const Eigen::Vector4f &p_src, const Eigen::Vector4f &p_tgt)
	Compute the squared Euclidean distance between two eigen vectors. More...

Function Documentation

computeMedian()

double pcl::distances::computeMedian ( double *  fvec, int  m  )

inline

Compute the median value from a set of doubles.

Parameters

[in]	fvec	the set of doubles
[in]	m	the number of doubles in the set

Definition at line 57 of file distances.h.

gedikli()

double pcl::distances::gedikli ( double  val, double  clipping, double  slope = 4  )

inline

Use a Gedikli kernel to estimate the distance between two vectors (for more information, see.

Parameters

[in]	val	the norm difference between two vectors
[in]	clipping	the clipping value
[in]	slope	the slope. Default: 4

Definition at line 107 of file distances.h.

huber() [1/2]

double pcl::distances::huber ( const Eigen::Vector4f &  p_src, const Eigen::Vector4f &  p_tgt, double  sigma  )

inline

Use a Huber kernel to estimate the distance between two vectors.

Parameters

[in]	p_src	the first eigen vector
[in]	p_tgt	the second eigen vector
[in]	sigma	the sigma value

Definition at line 72 of file distances.h.

huber() [2/2]

double pcl::distances::huber ( double  diff, double  sigma  )

inline

Use a Huber kernel to estimate the distance between two vectors.

Parameters

[in]	diff	the norm difference between two vectors
[in]	sigma	the sigma value

Definition at line 90 of file distances.h.

l1()

double pcl::distances::l1 ( const Eigen::Vector4f &  p_src, const Eigen::Vector4f &  p_tgt  )

inline

Compute the Manhattan distance between two eigen vectors.

Parameters

[in]	p_src	the first eigen vector
[in]	p_tgt	the second eigen vector

Definition at line 117 of file distances.h.

l2()

double pcl::distances::l2 ( const Eigen::Vector4f &  p_src, const Eigen::Vector4f &  p_tgt  )

inline

Compute the Euclidean distance between two eigen vectors.

Parameters

[in]	p_src	the first eigen vector
[in]	p_tgt	the second eigen vector

Definition at line 127 of file distances.h.

l2Sqr()

double pcl::distances::l2Sqr ( const Eigen::Vector4f &  p_src, const Eigen::Vector4f &  p_tgt  )

inline

Compute the squared Euclidean distance between two eigen vectors.

Parameters

[in]	p_src	the first eigen vector
[in]	p_tgt	the second eigen vector

Definition at line 137 of file distances.h.