#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 | |
| 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 |
Squared Euclidean distance functor, optimized version
| typedef True cvflann::L2< T >::is_kdtree_distance |
| typedef True cvflann::L2< T >::is_vector_space_distance |
| typedef T cvflann::L2< T >::ElementType |
| typedef Accumulator<T>::Type cvflann::L2< T >::ResultType |
| ResultType cvflann::L2< T >::operator() | ( | Iterator1 | a, |
| Iterator2 | b, | ||
| size_t | size, | ||
| ResultType | worst_dist = -1 |
||
| ) | const |
Compute the squared Euclidean 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::L2< T >::accum_dist | ( | const U & | a, |
| const V & | b, | ||
| int | |||
| ) | const |
Partial euclidean distance, using just one dimension. This is used by the kd-tree when computing partial distances while traversing the tree.
Squared root is omitted for efficiency.