Functions | |
| double | computeMedian (double *fvec, int m) |
| Compute the median value from a set of doubles. | |
| double | gedikli (double val, double clipping, double slope=4) |
| Use a Gedikli kernel to estimate the distance between two vectors (for more information, see. | |
| 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. | |
| double | huber (double diff, double sigma) |
| Use a Huber kernel to estimate the distance between two vectors. | |
| double | l1 (const Eigen::Vector4f &p_src, const Eigen::Vector4f &p_tgt) |
| Compute the Manhattan distance between two eigen vectors. | |
| double | l2 (const Eigen::Vector4f &p_src, const Eigen::Vector4f &p_tgt) |
| Compute the Euclidean distance between two eigen vectors. | |
| double | l2Sqr (const Eigen::Vector4f &p_src, const Eigen::Vector4f &p_tgt) |
| Compute the squared Euclidean distance between two eigen vectors. | |
| double pcl::distances::computeMedian | ( | double * | fvec, |
| int | m | ||
| ) | [inline] |
Compute the median value from a set of doubles.
| [in] | fvec | the set of doubles |
| [in] | m | the number of doubles in the set |
Definition at line 55 of file registration/include/pcl/registration/distances.h.
| 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.
| [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 registration/include/pcl/registration/distances.h.
| 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.
| [in] | p_src | the first eigen vector |
| [in] | p_tgt | the second eigen vector |
| [in] | sigma | the sigma value |
Definition at line 71 of file registration/include/pcl/registration/distances.h.
| double pcl::distances::huber | ( | double | diff, |
| double | sigma | ||
| ) | [inline] |
Use a Huber kernel to estimate the distance between two vectors.
| [in] | diff | the norm difference between two vectors |
| [in] | sigma | the sigma value |
Definition at line 90 of file registration/include/pcl/registration/distances.h.
| double pcl::distances::l1 | ( | const Eigen::Vector4f & | p_src, |
| const Eigen::Vector4f & | p_tgt | ||
| ) | [inline] |
Compute the Manhattan distance between two eigen vectors.
| [in] | p_src | the first eigen vector |
| [in] | p_tgt | the second eigen vector |
Definition at line 117 of file registration/include/pcl/registration/distances.h.
| double pcl::distances::l2 | ( | const Eigen::Vector4f & | p_src, |
| const Eigen::Vector4f & | p_tgt | ||
| ) | [inline] |
Compute the Euclidean distance between two eigen vectors.
| [in] | p_src | the first eigen vector |
| [in] | p_tgt | the second eigen vector |
Definition at line 127 of file registration/include/pcl/registration/distances.h.
| double pcl::distances::l2Sqr | ( | const Eigen::Vector4f & | p_src, |
| const Eigen::Vector4f & | p_tgt | ||
| ) | [inline] |
Compute the squared Euclidean distance between two eigen vectors.
| [in] | p_src | the first eigen vector |
| [in] | p_tgt | the second eigen vector |
Definition at line 137 of file registration/include/pcl/registration/distances.h.