Class cv::saliency::StaticSaliency#

#include <opencv2/saliency/saliencyBaseClasses.hpp>

Collaboration diagram for cv::saliency::StaticSaliency:

cv::saliency::StaticSaliency Node1 cv::saliency::StaticSaliency   + computeBinaryMap() # computeSaliencyImpl() Node2 cv::saliency::Saliency   + ~Saliency() + computeSaliency() # computeSaliencyImpl() Node2->Node1 Node3 cv::Algorithm   + Algorithm() + ~Algorithm() + clear() + empty() + getDefaultName() + read() + save() + write() + write() + load() + loadFromString() + read() # writeFormat() Node3->Node2 Node4 std::string     Node4->Node2 #className Node5 std::basic_string< Char >     Node5->Node4

cv::saliency::StaticSaliency Node1 cv::saliency::StaticSaliency   + computeBinaryMap() # computeSaliencyImpl() Node2 cv::saliency::Saliency   + ~Saliency() + computeSaliency() # computeSaliencyImpl() Node2->Node1 Node3 cv::Algorithm   + Algorithm() + ~Algorithm() + clear() + empty() + getDefaultName() + read() + save() + write() + write() + load() + loadFromString() + read() # writeFormat() Node3->Node2 Node4 std::string     Node4->Node2 #className Node5 std::basic_string< Char >     Node5->Node4

Public Member Functions#

Public Member Functions inherited from cv::saliency::Saliency

Return

Name

Description

~Saliency()

Destructor.

bool

computeSaliency(
    InputArray image,
    OutputArray saliencyMap )

Compute the saliency.
Public Member Functions inherited from cv::Algorithm

Return

Name

Description

Algorithm()

~Algorithm()

void

clear()

Clears the algorithm state.

bool

empty()

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.

String

getDefaultName()

void

read(const FileNode & fn)

Reads algorithm parameters from a file storage.

void

save(const String & filename)

void

write(
    const Ptr< FileStorage > & fs,
    const String & name = String() )

void

write(FileStorage & fs)

Stores algorithm parameters in a file storage.

void

write(
    FileStorage & fs,
    const String & name )

Static Public Member Functions#

Static Public Member Functions inherited from cv::Algorithm

Return

Name

Description

static Ptr< _Tp >

load(
    const String & filename,
    const String & objname = String() )

Loads algorithm from the file.

static Ptr< _Tp >

loadFromString(
    const String & strModel,
    const String & objname = String() )

Loads algorithm from a String.

static Ptr< _Tp >

read(const FileNode & fn)

Reads algorithm from the file node.

Additional Inherited Members#

Protected Member Functions inherited from cv::saliency::Saliency

Return

Name

Description

bool

computeSaliencyImpl(
    InputArray image,
    OutputArray saliencyMap )

Protected Member Functions inherited from cv::Algorithm

Return

Name

Description

void

writeFormat(FileStorage & fs)

Protected Attributes inherited from cv::saliency::Saliency

Return

Name

Description

String

className

Member Function Documentation#

computeBinaryMap()#

bool cv::saliency::StaticSaliency::computeBinaryMap(
InputArray _saliencyMap,
OutputArray _binaryMap )

Python:

cv.saliency.StaticSaliency.computeBinaryMap(_saliencyMap[, _binaryMap]) -> retval, _binaryMap

This function perform a binary map of given saliency map. This is obtained in this way:

In a first step, to improve the definition of interest areas and facilitate identification of targets, a segmentation by clustering is performed, using K-means algorithm. Then, to gain a binary representation of clustered saliency map, since values of the map can vary according to the characteristics of frame under analysis, it is not convenient to use a fixed threshold. So, Otsu’s algorithm* is used, which assumes that the image to be thresholded contains two classes of pixels or bi-modal histograms (e.g. foreground and back-ground pixels); later on, the algorithm calculates the optimal threshold separating those two classes, so that their intra-class variance is minimal.

Parameters

  • _saliencyMap — the saliency map obtained through one of the specialized algorithms

  • _binaryMap — the binary map

computeSaliencyImpl()#

bool cv::saliency::StaticSaliency::computeSaliencyImpl(
InputArray image,
OutputArray saliencyMap )

Source file#

The documentation for this class was generated from the following file: