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Class: vision.KalmanFilter
Package: vision

Prediction of measurement


[z_pred, x_pred, P_pred] = predict(obj)
[z_pred, x_pred, P_pred] = predict(obj,t)
[z_pred, x_pred, P_pred] = predict(obj,t,u)


[z_pred, x_pred, P_pred] = predict(obj) returns the prediction of measurement, state, and state estimation error covariance at the next time step (e.g., the next video frame). The object overwrites the internal state and covariance of the Kalman filter with the prediction results.

[z_pred, x_pred, P_pred] = predict(obj,t) additionally, lets you specify the time t, a positive integer. The returned values are the measurement, state, and state estimation error covariance predicted for t time steps (e.g., t video frames) later.

[z_pred, x_pred, P_pred] = predict(obj,t,u) additionally lets you specify the control input, u, an L-element vector. This syntax applies when you set the control model, B.

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