| OpenCV 3.4.3 Open Source Computer Vision

Public Member Functions | List of all members
cv::tracking::UnscentedKalmanFilter Class Referenceabstract

The interface for Unscented Kalman filter and Augmented Unscented Kalman filter. More...

`#include "kalman_filters.hpp"`

## Public Member Functions
virtual | ~UnscentedKalmanFilter ()
virtual Mat | correct (InputArray measurement)=0
virtual Mat | getErrorCov () const =0
virtual Mat | getMeasurementNoiseCov () const =0
virtual Mat | getProcessNoiseCov () const =0
virtual Mat | getState () const =0
virtual Mat | predict (InputArray control=noArray())=0

## Detailed Description

The interface for Unscented Kalman filter and Augmented Unscented Kalman filter.

## Constructor & Destructor Documentation

## § ~UnscentedKalmanFilter()

virtual cv::tracking::UnscentedKalmanFilter::~UnscentedKalmanFilter | ( |  | ) |
| inline virtual

## Member Function Documentation

## § correct()

virtual Mat cv::tracking::UnscentedKalmanFilter::correct | ( | InputArray | measurement | ) |
| pure virtual

The function performs correction step of the algorithm

Parameters

  measurement | - the current measurement vector,

Returns
  the corrected estimate of the state.

## § getErrorCov()

virtual Mat cv::tracking::UnscentedKalmanFilter::getErrorCov | ( |  | ) | const
| pure virtual

Returns
  the error cross-covariance matrix.

## § getMeasurementNoiseCov()

virtual Mat cv::tracking::UnscentedKalmanFilter::getMeasurementNoiseCov | ( |  | ) | const
| pure virtual

Returns
  the measurement noise cross-covariance matrix.

## § getProcessNoiseCov()

virtual Mat cv::tracking::UnscentedKalmanFilter::getProcessNoiseCov | ( |  | ) | const
| pure virtual

Returns
  the process noise cross-covariance matrix.

## § getState()

virtual Mat cv::tracking::UnscentedKalmanFilter::getState | ( |  | ) | const
| pure virtual

Returns
  the current estimate of the state.

## § predict()

virtual Mat cv::tracking::UnscentedKalmanFilter::predict | ( | InputArray | control = `noArray()` | ) |
| pure virtual

The function performs prediction step of the algorithm

Parameters

  control | - the current control vector,

Returns
  the predicted estimate of the state.

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

- /build/3_4-contrib_docs-lin64/opencv_contrib/modules/tracking/include/opencv2/tracking/kalman_filters.hpp