Class cv::legacy::TrackerKCF#

the [138] (Kernelized Correlation Filter) tracker View details

#include <opencv2/tracking/tracking_legacy.hpp>

Collaboration diagram for cv::legacy::TrackerKCF:

cv::legacy::TrackerKCF Node1 cv::legacy::TrackerKCF   + ~TrackerKCF() + setFeatureExtractor() + create() + create() Node2 cv::legacy::Tracker   + Tracker() + ~Tracker() + init() + read() + update() + write() # initImpl() # updateImpl() Node2->Node1 Node3 cv::Algorithm   + Algorithm() + ~Algorithm() + clear() + empty() + getDefaultName() + read() + save() + write() + write() + load() + loadFromString() + read() # writeFormat() Node3->Node2 Node4 bool     Node4->Node2 #isInit Node5 Ptr< cv::detail::tracking ::TrackerContribFeatureSet >     Node5->Node2 #featureSet Node6 Ptr< cv::detail::tracking ::TrackerContribSampler >     Node6->Node2 #sampler Node7 Ptr< cv::detail::tracking ::TrackerModel >     Node7->Node2 #model

cv::legacy::TrackerKCF Node1 cv::legacy::TrackerKCF   + ~TrackerKCF() + setFeatureExtractor() + create() + create() Node2 cv::legacy::Tracker   + Tracker() + ~Tracker() + init() + read() + update() + write() # initImpl() # updateImpl() Node2->Node1 Node3 cv::Algorithm   + Algorithm() + ~Algorithm() + clear() + empty() + getDefaultName() + read() + save() + write() + write() + load() + loadFromString() + read() # writeFormat() Node3->Node2 Node4 bool     Node4->Node2 #isInit Node5 Ptr< cv::detail::tracking ::TrackerContribFeatureSet >     Node5->Node2 #featureSet Node6 Ptr< cv::detail::tracking ::TrackerContribSampler >     Node6->Node2 #sampler Node7 Ptr< cv::detail::tracking ::TrackerModel >     Node7->Node2 #model

Public Member Functions#

Public Member Functions inherited from cv::legacy::Tracker

Return

Name

Description

Tracker()

~Tracker()

bool

init(
    InputArray image,
    const Rect2d & boundingBox )

Initialize the tracker with a known bounding box that surrounded the target.

void

read(const FileNode & fn)

Reads algorithm parameters from a file storage.

bool

update(
    InputArray image,
    Rect2d & boundingBox )

Update the tracker, find the new most likely bounding box for the target.

void

write(FileStorage & fs)

Stores algorithm parameters in a file storage.
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::legacy::Tracker

Return

Name

Description

bool

initImpl(
    const Mat & image,
    const Rect2d & boundingBox )

bool

updateImpl(
    const Mat & image,
    Rect2d & boundingBox )

Protected Member Functions inherited from cv::Algorithm

Return

Name

Description

void

writeFormat(FileStorage & fs)

Protected Attributes inherited from cv::legacy::Tracker

Return

Name

Description

Ptr< TrackerContribFeatureSet >

featureSet

bool

isInit

Ptr< TrackerModel >

model

Ptr< TrackerContribSampler >

sampler

Detailed Description#

the KCF (Kernelized Correlation Filter) tracker

KCF is a novel tracking framework that utilizes properties of circulant matrix to enhance the processing speed. This tracking method is an implementation of KCF_ECCV which is extended to KCF with color-names features (KCF_CN). The original paper of KCF is available at http://www.robots.ox.ac.uk/~joao/publications/henriques_tpami2015.pdf as well as the matlab implementation. For more information about KCF with color-names features, please refer to http://www.cvl.isy.liu.se/research/objrec/visualtracking/colvistrack/index.html.

Member Typedef Documentation#

MODE#

typedef enum cv::tracking::TrackerKCF::MODE cv::legacy::TrackerKCF::MODE

Feature type to be used in the tracking grayscale, colornames, compressed color-names The modes available now:

  • “GRAY” Use grayscale values as the feature

  • “CN” Color-names feature

Constructor & Destructor Documentation#

~TrackerKCF()#

cv::legacy::TrackerKCF::~TrackerKCF()

Member Function Documentation#

setFeatureExtractor()#

void cv::legacy::TrackerKCF::setFeatureExtractor(
void(*)(const Mat, const Rect, Mat &) ,
bool pca_func = false )

create()#

static Ptr< legacy::TrackerKCF > cv::legacy::TrackerKCF::create()

Python:

cv.legacy.TrackerKCF.create() -> retval

cv.legacy.TrackerKCF_create() -> retval

create()#

static Ptr< legacy::TrackerKCF > cv::legacy::TrackerKCF::create(const TrackerKCF::Params & parameters)

Python:

cv.legacy.TrackerKCF.create() -> retval

cv.legacy.TrackerKCF_create() -> retval

Constructor.

Parameters

Source file#

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