Trait KalmanFilterTrait 

pub trait KalmanFilterTrait: KalmanFilterTraitConst {
    // Required method
    fn as_raw_mut_KalmanFilter(&mut self) -> *mut c_void;

    // Provided methods
    fn set_state_pre(&mut self, val: Mat) { ... }
    fn set_state_post(&mut self, val: Mat) { ... }
    fn set_transition_matrix(&mut self, val: Mat) { ... }
    fn set_control_matrix(&mut self, val: Mat) { ... }
    fn set_measurement_matrix(&mut self, val: Mat) { ... }
    fn set_process_noise_cov(&mut self, val: Mat) { ... }
    fn set_measurement_noise_cov(&mut self, val: Mat) { ... }
    fn set_error_cov_pre(&mut self, val: Mat) { ... }
    fn set_gain(&mut self, val: Mat) { ... }
    fn set_error_cov_post(&mut self, val: Mat) { ... }
    fn set_temp1(&mut self, val: Mat) { ... }
    fn set_temp2(&mut self, val: Mat) { ... }
    fn set_temp3(&mut self, val: Mat) { ... }
    fn set_temp4(&mut self, val: Mat) { ... }
    fn set_temp5(&mut self, val: Mat) { ... }
    fn init(
        &mut self,
        dynam_params: i32,
        measure_params: i32,
        control_params: i32,
        typ: i32,
    ) -> Result<()> { ... }
    fn init_def(&mut self, dynam_params: i32, measure_params: i32) -> Result<()> { ... }
    fn predict(&mut self, control: &impl MatTraitConst) -> Result<Mat> { ... }
    fn predict_def(&mut self) -> Result<Mat> { ... }
    fn correct(&mut self, measurement: &impl MatTraitConst) -> Result<Mat> { ... }
}

Mutable methods for crate::video::KalmanFilter

Required Methods

fn as_raw_mut_KalmanFilter(&mut self) -> *mut c_void

Provided Methods

fn set_state_pre(&mut self, val: Mat)

predicted state (x’(k)): x(k)=Ax(k-1)+Bu(k)

fn set_state_post(&mut self, val: Mat)

corrected state (x(k)): x(k)=x’(k)+K(k)(z(k)-Hx’(k))

fn set_transition_matrix(&mut self, val: Mat)

state transition matrix (A)

fn set_control_matrix(&mut self, val: Mat)

control matrix (B) (not used if there is no control)

fn set_measurement_matrix(&mut self, val: Mat)

measurement matrix (H)

fn set_process_noise_cov(&mut self, val: Mat)

process noise covariance matrix (Q)

fn set_measurement_noise_cov(&mut self, val: Mat)

measurement noise covariance matrix (R)

fn set_error_cov_pre(&mut self, val: Mat)

priori error estimate covariance matrix (P’(k)): P’(k)=A*P(k-1)*At + Q)

fn set_gain(&mut self, val: Mat)

Kalman gain matrix (K(k)): K(k)=P’(k)Htinv(H*P’(k)*Ht+R)

fn set_error_cov_post(&mut self, val: Mat)

posteriori error estimate covariance matrix (P(k)): P(k)=(I-K(k)*H)*P’(k)

fn set_temp1(&mut self, val: Mat)

fn set_temp2(&mut self, val: Mat)

fn set_temp3(&mut self, val: Mat)

fn set_temp4(&mut self, val: Mat)

fn set_temp5(&mut self, val: Mat)

fn init( &mut self, dynam_params: i32, measure_params: i32, control_params: i32, typ: i32, ) -> Result<()>

Re-initializes Kalman filter. The previous content is destroyed.

Parameters

• dynamParams: Dimensionality of the state.
• measureParams: Dimensionality of the measurement.
• controlParams: Dimensionality of the control vector.
• type: Type of the created matrices that should be CV_32F or CV_64F.

C++ default parameters

• control_params: 0
• typ: CV_32F

fn init_def(&mut self, dynam_params: i32, measure_params: i32) -> Result<()>

Re-initializes Kalman filter. The previous content is destroyed.

Parameters

• dynamParams: Dimensionality of the state.
• measureParams: Dimensionality of the measurement.
• controlParams: Dimensionality of the control vector.
• type: Type of the created matrices that should be CV_32F or CV_64F.

Note

This alternative version of KalmanFilterTrait::init function uses the following default values for its arguments:

• control_params: 0
• typ: CV_32F

fn predict(&mut self, control: &impl MatTraitConst) -> Result<Mat>

Computes a predicted state.

Parameters

• control: The optional input control

C++ default parameters

• control: Mat()

fn predict_def(&mut self) -> Result<Mat>

Computes a predicted state.

Parameters

• control: The optional input control

Note

This alternative version of KalmanFilterTrait::predict function uses the following default values for its arguments:

• control: Mat()

fn correct(&mut self, measurement: &impl MatTraitConst) -> Result<Mat>

Updates the predicted state from the measurement.

Parameters

• measurement: The measured system parameters

Dyn Compatibility

This trait is not dyn compatible.

In older versions of Rust, dyn compatibility was called "object safety", so this trait is not object safe.

Implementors

impl KalmanFilterTrait for BoxedRefMut<'_, KalmanFilter>

impl KalmanFilterTrait for KalmanFilter