Class cv::detail::UnscentedKalmanFilterParams#

Unscented Kalman filter parameters. The class for initialization parameters of Unscented Kalman filter.

#include <opencv2/tracking/kalman_filters.hpp>

Collaboration diagram for cv::detail::UnscentedKalmanFilterParams:

cv::detail::tracking::kalman_filters::UnscentedKalmanFilterParams Node1 cv::detail::tracking ::kalman_filters::Unscented KalmanFilterParams   + UnscentedKalmanFilterParams() + UnscentedKalmanFilterParams() + init() Node2 int     Node2->Node1 +CP +DP +MP +dataType Node3 cv::Mat   + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() and 152 more... + diag() + eye() + eye() + getDefaultAllocator() + getStdAllocator() + ones() + ones() + ones() + ones() + setDefaultAllocator() + zeros() + zeros() + zeros() + zeros() # forEach_impl() Node2->Node3 +cols +dims +dummy +flags +rows Node3->Node1 +errorCovInit +measurementNoiseCov +processNoiseCov +stateInit Node4 uint8_t     Node4->Node3 +data +dataend +datalimit +datastart Node5 cv::MatAllocator   + MatAllocator() + ~MatAllocator() + allocate() + allocate() + copy() + deallocate() + download() + getBufferPoolController() + map() + unmap() + upload() Node5->Node3 +allocator Node6 UMatData *     Node6->Node3 +u Node7 MatSize     Node7->Node3 +size Node8 MatStep     Node8->Node3 +step Node9 double     Node9->Node1 +alpha +beta +k Node10 Ptr< cv::detail::tracking ::kalman_filters::UkfSystemModel >     Node10->Node1 +model

cv::detail::tracking::kalman_filters::UnscentedKalmanFilterParams Node1 cv::detail::tracking ::kalman_filters::Unscented KalmanFilterParams   + UnscentedKalmanFilterParams() + UnscentedKalmanFilterParams() + init() Node2 int     Node2->Node1 +CP +DP +MP +dataType Node3 cv::Mat   + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() and 152 more... + diag() + eye() + eye() + getDefaultAllocator() + getStdAllocator() + ones() + ones() + ones() + ones() + setDefaultAllocator() + zeros() + zeros() + zeros() + zeros() # forEach_impl() Node2->Node3 +cols +dims +dummy +flags +rows Node3->Node1 +errorCovInit +measurementNoiseCov +processNoiseCov +stateInit Node4 uint8_t     Node4->Node3 +data +dataend +datalimit +datastart Node5 cv::MatAllocator   + MatAllocator() + ~MatAllocator() + allocate() + allocate() + copy() + deallocate() + download() + getBufferPoolController() + map() + unmap() + upload() Node5->Node3 +allocator Node6 UMatData *     Node6->Node3 +u Node7 MatSize     Node7->Node3 +size Node8 MatStep     Node8->Node3 +step Node9 double     Node9->Node1 +alpha +beta +k Node10 Ptr< cv::detail::tracking ::kalman_filters::UkfSystemModel >     Node10->Node1 +model

Detailed Description#

Unscented Kalman filter parameters. The class for initialization parameters of Unscented Kalman filter.

Constructor & Destructor Documentation#

UnscentedKalmanFilterParams()#

cv::detail::UnscentedKalmanFilterParams::UnscentedKalmanFilterParams()

The constructors.

UnscentedKalmanFilterParams()#

cv::detail::UnscentedKalmanFilterParams::UnscentedKalmanFilterParams(
int dp,
int mp,
int cp,
double processNoiseCovDiag,
double measurementNoiseCovDiag,
Ptr< UkfSystemModel > dynamicalSystem,
int type = CV_64F )

Parameters

  • dp — - dimensionality of the state vector,

  • mp — - dimensionality of the measurement vector,

  • cp — - dimensionality of the control vector,

  • processNoiseCovDiag — - value of elements on main diagonal process noise cross-covariance matrix,

  • measurementNoiseCovDiag — - value of elements on main diagonal measurement noise cross-covariance matrix,

  • dynamicalSystem — - ptr to object of the class containing functions for computing the next state and the measurement,

  • type — - type of the created matrices that should be CV_32F or CV_64F.

Member Function Documentation#

init()#

void cv::detail::UnscentedKalmanFilterParams::init(
int dp,
int mp,
int cp,
double processNoiseCovDiag,
double measurementNoiseCovDiag,
Ptr< UkfSystemModel > dynamicalSystem,
int type = CV_64F )

The function for initialization of Unscented Kalman filter

Parameters

  • dp — - dimensionality of the state vector,

  • mp — - dimensionality of the measurement vector,

  • cp — - dimensionality of the control vector,

  • processNoiseCovDiag — - value of elements on main diagonal process noise cross-covariance matrix,

  • measurementNoiseCovDiag — - value of elements on main diagonal measurement noise cross-covariance matrix,

  • dynamicalSystem — - ptr to object of the class containing functions for computing the next state and the measurement,

  • type — - type of the created matrices that should be CV_32F or CV_64F.

Member Data Documentation#

alpha#

double cv::detail::UnscentedKalmanFilterParams::alpha

Default is 1e-3.

beta#

double cv::detail::UnscentedKalmanFilterParams::beta

Default is 2.0.

CP#

int cv::detail::UnscentedKalmanFilterParams::CP

Dimensionality of the control vector.

dataType#

int cv::detail::UnscentedKalmanFilterParams::dataType

Type of elements of vectors and matrices, default is CV_64F.

DP#

int cv::detail::UnscentedKalmanFilterParams::DP

Dimensionality of the state vector.

errorCovInit#

Mat cv::detail::UnscentedKalmanFilterParams::errorCovInit

State estimate cross-covariance matrix, DP x DP, default is identity.

k#

double cv::detail::UnscentedKalmanFilterParams::k

Default is 0.

measurementNoiseCov#

Mat cv::detail::UnscentedKalmanFilterParams::measurementNoiseCov

Measurement noise cross-covariance matrix, MP x MP.

model#

Ptr< UkfSystemModel > cv::detail::UnscentedKalmanFilterParams::model

Object of the class containing functions for computing the next state and the measurement.

MP#

int cv::detail::UnscentedKalmanFilterParams::MP

Dimensionality of the measurement vector.

processNoiseCov#

Mat cv::detail::UnscentedKalmanFilterParams::processNoiseCov

Process noise cross-covariance matrix, DP x DP.

stateInit#

Mat cv::detail::UnscentedKalmanFilterParams::stateInit

Initial state, DP x 1, default is zero.

Source file#

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