- All Known Implementing Classes:
public interface TupleMapDistanceNorm
Generalized way for normalizing and computing the distance between two sparse descriptors in a map format. Intended for use with
RecognitionVocabularyTreeNister2006. Uses efficient distance formula from .
 Nister, David, and Henrik Stewenius. "Scalable recognition with a vocabulary tree." 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06). Vol. 2. Ieee, 2006.
Nested Class SummaryModifier and TypeInterfaceDescription
static classL1-norm for scoring
static classL2-norm for scoring
static enumDistance functions that are supported
Method SummaryModifier and TypeMethodDescription
(float valA, float valB)Incremental update to the distance.Create a new instance that is thread safe, i.e.
(DogArray_F32 weights)Normalizes the descriptor.
(DogArray_F32 weights)Normalizes the descriptor. Computes the norm then divides each element by the norm.
(float valA, float valB)Incremental update to the distance. Initially the distance is set to 2.0, then for every word that is present in both descriptors add this value to it. This only works for a subclass of normalizations. See  for details.
newInstanceThreadTupleMapDistanceNorm newInstanceThread()Create a new instance that is thread safe, i.e. read only settings can be shared