[37] | 1 | %this is a script to test the self calibration stuff
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| 2 | %torr_test_calib_sc.m
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| 3 | %main()
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| 4 | %profile on
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| 5 | clear all;
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| 6 | m3 = 256;
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| 7 | method = 'mapsac';
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| 8 | %method = 'linear';
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| 9 |
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| 10 |
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| 11 | % % do we want the same result each time
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| 12 | % randn('state',0)
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| 13 | % rand('state',0)
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| 14 | no_test = 1;
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| 15 | for(i = 1:no_test)
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| 16 |
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| 17 | % [true_F,x1,y1,x2,y2,nx1,ny1,nx2,ny2] = ...
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| 18 | % torr_gen_2view_matches(foc, no_matches, noise_sigma, translation_mult, translation_adder, ...
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| 19 | % rotation_multplier, min_Z,Z_RAN,m3);
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| 20 | [true_F,x1,y1,x2,y2,nx1,ny1,nx2,ny2,true_C,true_R,true_TX, true_E] = torr_gen_2view_matches;
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| 21 |
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| 22 | % m3 = 256
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| 23 | x_a = [x1,y1,repmat(m3,length(x1),1)];
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| 24 | x_a_prime = [x2,y2,repmat(m3,length(x1),1)];
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| 25 |
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| 26 | err_calc_a = [];
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| 27 | for k = 1:length(x1),
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| 28 | err_calc_a = [err_calc_a; (x_a_prime(k,:)) * true_F * (x_a(k,:)')];
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| 29 | end
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| 30 |
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| 31 | %total sum of error
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| 32 | disp('======================================================================');
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| 33 | disp(sprintf('Sum of squared error for true_F: x_prime*F*x = %d',sum(err_calc_a.^2)));
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| 34 | disp('======================================================================');
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| 35 |
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| 36 | no_matches = length(nx1);
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| 37 |
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| 38 | %if we set this to one then the result should be the same as the groundtruth...
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| 39 | no_noise = 1;
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| 40 | if (no_noise)
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| 41 | disp('just using noise free points');
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| 42 | nx1 = x1;
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| 43 | nx2 = x2;
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| 44 | ny1 = y1;
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| 45 | ny2 = y2;
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| 46 | end
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| 47 |
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| 48 |
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| 49 |
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| 50 | matches = [nx1,ny1,nx2,ny2];
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| 51 | perfect_matches = [x1,y1,x2,y2];
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| 52 | set_rank2 = 1;
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| 53 |
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| 54 | %first estimate F
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| 55 | %disp('First Match');
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| 56 | %matches(1,:)
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| 57 | [f, e1, n_inliers,inlier_index,nF] = torr_estimateF( perfect_matches, m3, [], method, set_rank2);
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| 58 |
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| 59 | x_b = [x1,y1,repmat(m3,length(x1),1)];
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| 60 | x_b_prime = [x2,y2,repmat(m3,length(x1),1)];
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| 61 |
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| 62 | err_calc_b = [];
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| 63 | for k = 1:length(x1),
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| 64 | err_calc_b = [err_calc_b; (x_a_prime(k,:)) * nF * (x_a(k,:)')];
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| 65 | end
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| 66 |
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| 67 | %total sum of error
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| 68 | disp('======================================================================');
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| 69 | disp(sprintf('Sum of squared error for mapsac nF: x_prime*nF*x = %d',sum(err_calc_b.^2)));
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| 70 | disp('======================================================================');
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| 71 |
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| 72 | end
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| 73 |
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| 74 |
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| 75 | method = 'linear';
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| 76 | %first estimate F
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| 77 | %disp('First Match');
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| 78 | %matches(1,:)
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| 79 | [f, e1, n_inliers,inlier_index,nF] = torr_estimateF( perfect_matches, m3, [], method, set_rank2);
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| 80 |
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| 81 | x_b = [x1,y1,repmat(m3,length(x1),1)];
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| 82 | x_b_prime = [x2,y2,repmat(m3,length(x1),1)];
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| 83 |
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| 84 | err_calc_b = [];
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| 85 | for k = 1:length(x1),
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| 86 | err_calc_b = [err_calc_b; (x_a_prime(k,:)) * nF * (x_a(k,:)')];
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| 87 | end
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| 88 |
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| 89 | %total sum of error
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| 90 | disp('======================================================================');
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| 91 | disp(sprintf('Sum of squared error for linear nF: x_prime*nF*x = %d',sum(err_calc_b.^2)));
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| 92 | disp('======================================================================');
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