42
#ifndef __OPENCV_TRACKING_KALMAN_HPP_
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#define __OPENCV_TRACKING_KALMAN_HPP_
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#include "opencv2/core.hpp"
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inline
namespace
tracking {
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inline
namespace
kalman_filters {
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virtual
Mat
predict( InputArray control = noArray() ) = 0;
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void
init(
int
dp,
int
mp,
int
cp,
double
processNoiseCovDiag,
double
measurementNoiseCovDiag,
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void
init(
int
dp,
int
mp,
int
cp,
double
processNoiseCovDiag,
double
measurementNoiseCovDiag,
n-dimensional dense array class
Definition:
mat.hpp:802
Augmented Unscented Kalman filter parameters. The class for initialization parameters of Augmented Un...
Definition:
kalman_filters.hpp:183
AugmentedUnscentedKalmanFilterParams(int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, Ptr< UkfSystemModel > dynamicalSystem, int type=CV_64F)
void init(int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, Ptr< UkfSystemModel > dynamicalSystem, int type=CV_64F)
Model of dynamical system for Unscented Kalman filter. The interface for dynamical system model....
Definition:
kalman_filters.hpp:103
virtual void measurementFunction(const Mat &x_k, const Mat &n_k, Mat &z_k)=0
virtual void stateConversionFunction(const Mat &x_k, const Mat &u_k, const Mat &v_k, Mat &x_kplus1)=0
The interface for Unscented Kalman filter and Augmented Unscented Kalman filter.
Definition:
kalman_filters.hpp:60
virtual Mat getState() const =0
virtual Mat getProcessNoiseCov() const =0
virtual Mat getErrorCov() const =0
virtual Mat correct(InputArray measurement)=0
virtual Mat getMeasurementNoiseCov() const =0
virtual Mat predict(InputArray control=noArray())=0
Unscented Kalman filter parameters. The class for initialization parameters of Unscented Kalman filte...
Definition:
kalman_filters.hpp:128
double k
Default is 0.
Definition:
kalman_filters.hpp:144
int CP
Dimensionality of the control vector.
Definition:
kalman_filters.hpp:133
double alpha
Default is 1e-3.
Definition:
kalman_filters.hpp:143
void init(int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, Ptr< UkfSystemModel > dynamicalSystem, int type=CV_64F)
Mat errorCovInit
State estimate cross-covariance matrix, DP x DP, default is identity.
Definition:
kalman_filters.hpp:137
Ptr< UkfSystemModel > model
Object of the class containing functions for computing the next state and the measurement.
Definition:
kalman_filters.hpp:148
UnscentedKalmanFilterParams(int dp, int mp, int cp, double processNoiseCovDiag, double measurementNoiseCovDiag, Ptr< UkfSystemModel > dynamicalSystem, int type=CV_64F)
int DP
Dimensionality of the state vector.
Definition:
kalman_filters.hpp:131
Mat measurementNoiseCov
Measurement noise cross-covariance matrix, MP x MP.
Definition:
kalman_filters.hpp:140
UnscentedKalmanFilterParams()
Definition:
kalman_filters.hpp:152
int MP
Dimensionality of the measurement vector.
Definition:
kalman_filters.hpp:132
int dataType
Type of elements of vectors and matrices, default is CV_64F.
Definition:
kalman_filters.hpp:134
Mat processNoiseCov
Process noise cross-covariance matrix, DP x DP.
Definition:
kalman_filters.hpp:139
Mat stateInit
Initial state, DP x 1, default is zero.
Definition:
kalman_filters.hpp:136
double beta
Default is 2.0.
Definition:
kalman_filters.hpp:145
"black box" representation of the file storage associated with a file on disk.
Definition:
aruco.hpp:75
Definition:
cvstd_wrapper.hpp:74