View Source Evision.KalmanFilter (Evision v0.1.8)
Link to this section Summary
cv
Updates the predicted state from the measurement.
Python prototype (for reference):
Positional Arguments
dynamParams:
int
.
Positional Arguments
dynamParams:
int
.
Computes a predicted state.
Functions
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Link to this section cv
Updates the predicted state from the measurement.
Positional Arguments
measurement:
Evision.Mat
.The measured system parameters
Python prototype (for reference):
correct(measurement) -> retval
Python prototype (for reference):
KalmanFilter() -> <KalmanFilter object>
Positional Arguments
dynamParams:
int
.Dimensionality of the state.
measureParams:
int
.Dimensionality of the measurement.
Keyword Arguments
controlParams:
int
.Dimensionality of the control vector.
type:
int
.Type of the created matrices that should be CV_32F or CV_64F.
Has overloading in C++
Python prototype (for reference):
KalmanFilter(dynamParams, measureParams[, controlParams[, type]]) -> <KalmanFilter object>
Positional Arguments
dynamParams:
int
.Dimensionality of the state.
measureParams:
int
.Dimensionality of the measurement.
Keyword Arguments
controlParams:
int
.Dimensionality of the control vector.
type:
int
.Type of the created matrices that should be CV_32F or CV_64F.
Has overloading in C++
Python prototype (for reference):
KalmanFilter(dynamParams, measureParams[, controlParams[, type]]) -> <KalmanFilter object>
Computes a predicted state.
Keyword Arguments
control:
Evision.Mat
.The optional input control
Python prototype (for reference):
predict([, control]) -> retval
Link to this section Functions
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