mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
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102 lines
3.3 KiB
102 lines
3.3 KiB
#! /usr/bin/env octave |
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## Tracking of rotating point. |
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## Rotation speed is constant. |
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## Both state and measurements vectors are 1D (a point angle), |
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## Measurement is the real point angle + gaussian noise. |
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## The real and the estimated points are connected with yellow line segment, |
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## the real and the measured points are connected with red line segment. |
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## (if Kalman filter works correctly, |
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## the yellow segment should be shorter than the red one). |
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## Pressing any key (except ESC) will reset the tracking with a different speed. |
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## Pressing ESC will stop the program. |
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cv; |
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highgui; |
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global img; |
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function ret=calc_point(angle) |
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global img; |
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ret=cvPoint( cvRound(img.width/2 + img.width/3*cos(angle)), \ |
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cvRound(img.height/2 - img.width/3*sin(angle))); |
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endfunction |
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function draw_cross( center, color, d ) |
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global img; |
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global CV_AA; |
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cvLine( img, cvPoint( center.x - d, center.y - d ), |
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cvPoint( center.x + d, center.y + d ), color, 1, CV_AA, 0); |
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cvLine( img, cvPoint( center.x + d, center.y - d ), |
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cvPoint( center.x - d, center.y + d ), \ |
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color, 1, CV_AA, 0 ); |
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endfunction |
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A = [ 1, 1; 0, 1 ]; |
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img = cvCreateImage( cvSize(500,500), 8, 3 ); |
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kalman = cvCreateKalman( 2, 1, 0 ); |
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state = cvCreateMat( 2, 1, CV_32FC1 ); # (phi, delta_phi) |
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process_noise = cvCreateMat( 2, 1, CV_32FC1 ); |
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measurement = cvCreateMat( 1, 1, CV_32FC1 ); |
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rng = cvRNG(-1); |
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code = -1; |
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cvZero( measurement ); |
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cvNamedWindow( "Kalman", 1 ); |
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while (true), |
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cvRandArr( rng, state, CV_RAND_NORMAL, cvRealScalar(0), cvRealScalar(0.1) ); |
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kalman.transition_matrix = mat2cv(A, CV_32FC1); |
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cvSetIdentity( kalman.measurement_matrix, cvRealScalar(1) ); |
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cvSetIdentity( kalman.process_noise_cov, cvRealScalar(1e-5) ); |
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cvSetIdentity( kalman.measurement_noise_cov, cvRealScalar(1e-1) ); |
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cvSetIdentity( kalman.error_cov_post, cvRealScalar(1)); |
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cvRandArr( rng, kalman.state_post, CV_RAND_NORMAL, cvRealScalar(0), cvRealScalar(0.1) ); |
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while (true), |
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state_angle = state(0); |
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state_pt = calc_point(state_angle); |
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prediction = cvKalmanPredict( kalman ); |
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predict_angle = prediction(0); |
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predict_pt = calc_point(predict_angle); |
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cvRandArr( rng, measurement, CV_RAND_NORMAL, cvRealScalar(0), \ |
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cvRealScalar(sqrt(kalman.measurement_noise_cov(0))) ); |
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## generate measurement |
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cvMatMulAdd( kalman.measurement_matrix, state, measurement, measurement ); |
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measurement_angle = measurement(0); |
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measurement_pt = calc_point(measurement_angle); |
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## plot points |
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cvZero( img ); |
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draw_cross( state_pt, CV_RGB(255,255,255), 3 ); |
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draw_cross( measurement_pt, CV_RGB(255,0,0), 3 ); |
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draw_cross( predict_pt, CV_RGB(0,255,0), 3 ); |
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cvLine( img, state_pt, measurement_pt, CV_RGB(255,0,0), 3, CV_AA, 0 ); |
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cvLine( img, state_pt, predict_pt, CV_RGB(255,255,0), 3, CV_AA, 0 ); |
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cvKalmanCorrect( kalman, measurement ); |
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cvRandArr( rng, process_noise, CV_RAND_NORMAL, cvRealScalar(0), \ |
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cvRealScalar(sqrt(kalman.process_noise_cov(0)(0)))); |
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cvMatMulAdd( kalman.transition_matrix, state, process_noise, state ); |
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cvShowImage( "Kalman", img ); |
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code = cvWaitKey( 100 ); |
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if( code > 0 ) |
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break; |
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endif |
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endwhile |
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if( code == '\x1b' || code == 'q' || code == 'Q' ) |
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break; |
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endif |
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endwhile |
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cvDestroyWindow("Kalman");
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