MTF
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base class for appearance models that use the negative sum of squared differences ("SSD") or L2 norm of the difference between the initial and current pixel values (original or modified) as the similarity measure More...
#include <SSDBase.h>
Public Types | |
typedef bool | is_kdtree_distance |
typedef double | ElementType |
typedef double | ResultType |
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typedef double | ElementType |
typedef double | ResultType |
Public Member Functions | |
SSDBaseDist (const string &_name) | |
double | operator() (const double *a, const double *b, size_t size, double worst_dist=-1) const override |
Squared Euclidean distance functor, optimized version. More... | |
double | accum_dist (const double &a, const double &b, int) const |
Partial euclidean distance, using just one dimension. More... | |
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AMDist (const string &_name) | |
Additional Inherited Members | |
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const string | name |
base class for appearance models that use the negative sum of squared differences ("SSD") or L2 norm of the difference between the initial and current pixel values (original or modified) as the similarity measure
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inline |
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.
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overridevirtual |
Squared Euclidean distance functor, optimized version.
Compute the squared Euclidean distance between two vectors.
This is highly optimized, 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.
Reimplemented from AMDist.