#include <dist.h>
Public Types | |
| typedef True | is_kdtree_distance |
| typedef True | is_vector_space_distance |
| typedef T | ElementType |
| typedef Accumulator< T >::Type | ResultType |
Public Member Functions | |
| MinkowskiDistance (int order_) | |
| template<typename Iterator1 , typename Iterator2 > | |
| ResultType | operator() (Iterator1 a, Iterator2 b, size_t size, ResultType worst_dist=-1) const |
| template<typename U , typename V > | |
| ResultType | accum_dist (const U &a, const V &b, int) const |
Public Attributes | |
| int | order |
| typedef True cvflann::MinkowskiDistance< T >::is_kdtree_distance |
| typedef True cvflann::MinkowskiDistance< T >::is_vector_space_distance |
| typedef T cvflann::MinkowskiDistance< T >::ElementType |
| typedef Accumulator<T>::Type cvflann::MinkowskiDistance< T >::ResultType |
| cvflann::MinkowskiDistance< T >::MinkowskiDistance | ( | int | order_ | ) |
| ResultType cvflann::MinkowskiDistance< T >::operator() | ( | Iterator1 | a, |
| Iterator2 | b, | ||
| size_t | size, | ||
| ResultType | worst_dist = -1 |
||
| ) | const |
Compute the Minkowsky (L_p) distance between two vectors.
This is highly optimised, with loop unrolling, as it is one of the most expensive inner loops.
The computation of squared root at the end is omitted for efficiency.
| ResultType cvflann::MinkowskiDistance< T >::accum_dist | ( | const U & | a, |
| const V & | b, | ||
| int | |||
| ) | const |
Partial distance, used by the kd-tree.
| int cvflann::MinkowskiDistance< T >::order |