template class cvflann::CompositeIndex

Overview

This index builds a kd-tree index and a k-means index and performs nearest neighbour search both indexes. More…

#include <composite_index.h>

template <typename Distance>
class CompositeIndex: public cvflann::NNIndex
{
public:
    // typedefs

    typedef Distance::ResultType DistanceType;
    typedef Distance::ElementType ElementType;

    // construction

    CompositeIndex(
        const Matrix<ElementType>& inputData,
        const IndexParams& params = CompositeIndexParams(),
        Distance d = Distance()
        );

    CompositeIndex(const CompositeIndex&);

    // methods

    virtual
    void
    buildIndex();

    virtual
    void
    findNeighbors(
        ResultSet<DistanceType>& result,
        const ElementType* vec,
        const SearchParams& searchParams
        );

    virtual
    IndexParams
    getParameters() const;

    virtual
    flann_algorithm_t
    getType() const;

    virtual
    void
    loadIndex(FILE* stream);

    CompositeIndex&
    operator=(const CompositeIndex&);

    virtual
    void
    saveIndex(FILE* stream);

    virtual
    size_t
    size() const;

    virtual
    int
    usedMemory() const;

    virtual
    size_t
    veclen() const;
};

Inherited Members

public:
    // methods

    virtual
    void
    buildIndex() = 0;

    virtual
    void
    findNeighbors(
        ResultSet<DistanceType>& result,
        const ElementType* vec,
        const SearchParams& searchParams
        ) = 0;

    virtual
    IndexParams
    getParameters() const = 0;

    virtual
    flann_algorithm_t
    getType() const = 0;

    virtual
    void
    knnSearch(
        const Matrix<ElementType>& queries,
        Matrix<int>& indices,
        Matrix<DistanceType>& dists,
        int knn,
        const SearchParams& params
        );

    virtual
    void
    loadIndex(FILE* stream) = 0;

    virtual
    int
    radiusSearch(
        const Matrix<ElementType>& query,
        Matrix<int>& indices,
        Matrix<DistanceType>& dists,
        float radius,
        const SearchParams& params
        );

    virtual
    void
    saveIndex(FILE* stream) = 0;

    virtual
    size_t
    size() const = 0;

    virtual
    int
    usedMemory() const = 0;

    virtual
    size_t
    veclen() const = 0;

Detailed Documentation

This index builds a kd-tree index and a k-means index and performs nearest neighbour search both indexes. This gives a slight boost in search performance as some of the neighbours that are missed by one index are found by the other.

Construction

CompositeIndex(
    const Matrix<ElementType>& inputData,
    const IndexParams& params = CompositeIndexParams(),
    Distance d = Distance()
    )

Index constructor

Parameters:

inputData	dataset containing the points to index
params	Index parameters
d	Distance functor

Returns:

Methods

virtual
void
buildIndex()

Builds the index.

virtual
void
findNeighbors(
    ResultSet<DistanceType>& result,
    const ElementType* vec,
    const SearchParams& searchParams
    )

Method that searches for nearest-neighbours.

virtual
IndexParams
getParameters() const

Returns:

The index parameters

virtual
flann_algorithm_t
getType() const

Returns:

The index type

virtual
void
loadIndex(FILE* stream)

Loads the index from a stream.

Parameters:

stream

The stream from which the index is loaded

virtual
void
saveIndex(FILE* stream)

Saves the index to a stream.

Parameters:

stream

The stream to save the index to

virtual
size_t
size() const

Returns:

Size of the index

virtual
int
usedMemory() const

Returns:

The amount of memory (in bytes) used by the index.

virtual
size_t
veclen() const

Returns:

The dimensionality of the features in this index.