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Open Source Computer Vision Library
https://opencv.org/
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104 lines
4.1 KiB
104 lines
4.1 KiB
/* |
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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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*/ |
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#include "opencv2/video/tracking.hpp" |
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#include "opencv2/highgui/highgui.hpp" |
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int main(int argc, char** argv) |
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{ |
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const float A[] = { 1, 1, 0, 1 }; |
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IplImage* img = cvCreateImage( cvSize(500,500), 8, 3 ); |
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CvKalman* kalman = cvCreateKalman( 2, 1, 0 ); |
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CvMat* state = cvCreateMat( 2, 1, CV_32FC1 ); /* (phi, delta_phi) */ |
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CvMat* process_noise = cvCreateMat( 2, 1, CV_32FC1 ); |
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CvMat* measurement = cvCreateMat( 1, 1, CV_32FC1 ); |
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CvRNG rng = cvRNG(-1); |
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char code = -1; |
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cvZero( measurement ); |
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cvNamedWindow( "Kalman", 1 ); |
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for(;;) |
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{ |
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cvRandArr( &rng, state, CV_RAND_NORMAL, cvRealScalar(0), cvRealScalar(0.1) ); |
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memcpy( kalman->transition_matrix->data.fl, A, sizeof(A)); |
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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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for(;;) |
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{ |
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#define calc_point(angle) \ |
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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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float state_angle = state->data.fl[0]; |
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CvPoint state_pt = calc_point(state_angle); |
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const CvMat* prediction = cvKalmanPredict( kalman, 0 ); |
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float predict_angle = prediction->data.fl[0]; |
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CvPoint predict_pt = calc_point(predict_angle); |
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float measurement_angle; |
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CvPoint measurement_pt; |
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cvRandArr( &rng, measurement, CV_RAND_NORMAL, cvRealScalar(0), |
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cvRealScalar(sqrt(kalman->measurement_noise_cov->data.fl[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->data.fl[0]; |
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measurement_pt = calc_point(measurement_angle); |
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/* plot points */ |
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#define draw_cross( center, color, d ) \ |
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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 ), color, 1, CV_AA, 0 ) |
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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->data.fl[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 = (char) cvWaitKey( 100 ); |
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if( code > 0 ) |
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break; |
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} |
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if( code == 27 || code == 'q' || code == 'Q' ) |
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break; |
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} |
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cvDestroyWindow("Kalman"); |
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return 0; |
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} |
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#ifdef _EiC |
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main(1, "kalman.c"); |
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#endif
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