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let Kalman handle the missing measurements (bug #1380)
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@ -171,6 +171,9 @@ cvKalmanPredict( CvKalman* kalman, const CvMat* control )
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/* P'(k) = temp1*At + Q */
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cvGEMM( kalman->temp1, kalman->transition_matrix, 1, kalman->process_noise_cov, 1,
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kalman->error_cov_pre, CV_GEMM_B_T );
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/* handle the case when there will be measurement before the next predict */
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cvCopy(kalman->state_pre, kalman->state_post);
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return kalman->state_pre;
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}
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@ -260,6 +263,9 @@ const Mat& KalmanFilter::predict(const Mat& control)
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// P'(k) = temp1*At + Q
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gemm(temp1, transitionMatrix, 1, processNoiseCov, 1, errorCovPre, GEMM_2_T);
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// handle the case when there will be measurement before the next predict.
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statePre.copyTo(statePost);
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return statePre;
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}
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@ -82,7 +82,8 @@ int main(int, char**)
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line( img, statePt, measPt, Scalar(0,0,255), 3, CV_AA, 0 );
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line( img, statePt, predictPt, Scalar(0,255,255), 3, CV_AA, 0 );
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KF.correct(measurement);
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if(theRNG().uniform(0,4) != 0)
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KF.correct(measurement);
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randn( processNoise, Scalar(0), Scalar::all(sqrt(KF.processNoiseCov.at<float>(0, 0))));
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state = KF.transitionMatrix*state + processNoise;
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