Namespaces | |
| namespace | distance |
Classes | |
| class | Database |
| Class for efficiently matching a bag-of-words representation of a document (image) against a database of known documents. More... | |
| struct | DefaultAllocator |
| Meta-function to get the default allocator for a particular feature type. More... | |
| struct | DefaultAllocator< Eigen::Matrix< Scalar, Rows, Cols, Options, MaxRows, MaxCols > > |
| class | GenericTree |
| Vocabulary tree wrapper for easy integration with OpenCV features, or when the (dense) descriptor size and/or type isn't known at compile time. More... | |
| struct | InitGiven |
| Dummy initializer for K-means that leaves the centers as-is. More... | |
| struct | InitRandom |
| Initializer for K-means that randomly selects k features as the cluster centers. More... | |
| struct | Match |
| Struct representing a single database match. More... | |
| class | MutableVocabularyTree |
| Vocabulary tree that exposes the hierarchical clustering centers. Mainly intended for building a new tree. More... | |
| class | SimpleKmeans |
| Class for performing K-means clustering, optimized for a particular feature type and metric. More... | |
| class | TreeBuilder |
| Class for building a new vocabulary by hierarchically clustering a set of training features. More... | |
| class | VocabularyTree |
| Optimized vocabulary tree quantizer, templated on feature type and distance metric for maximum efficiency. More... | |
Typedefs | |
| typedef uint32_t | DocId |
| typedef std::vector< Word > | Document |
| typedef std::vector< Match > | Matches |
| typedef int32_t | Word |
| typedef uint32_t vt::DocId |
Definition at line 10 of file database.h.
| typedef std::vector<Word> vt::Document |
Definition at line 33 of file database.h.
| typedef std::vector<Match> vt::Matches |
Definition at line 34 of file database.h.
| typedef int32_t vt::Word |
Definition at line 16 of file vocabulary_tree.h.