[37] | 1 | function [err, aff_err, stable] = real_intensity(s) |
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| 2 | % fo = fraction of frames points are occluded. |
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| 3 | % nframes = number frames |
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| 4 | % npoints = number points |
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| 5 | % frot = fraction of 2*pi for rotation in depth. |
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| 6 | % sigma = magnitude of Gaussian error. Pt. coordinates typically range |
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| 7 | % between -1 and 1, so a reasonable setting might be .01, or .005. |
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| 8 | % s = number of samples to draw in my method. |
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| 9 | % n = number times to repeat exp. |
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| 10 | |
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| 11 | % there are a number of other parameters set in these experiments. |
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| 12 | % In motion generation, there is amount of translation (0) and in-plane rotation. |
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| 13 | % in shum there are the number of iterations to try. |
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| 14 | |
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| 15 | num_random_starts = 5; |
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| 16 | |
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| 17 | test2_data; |
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| 18 | M = test2_im_data; |
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| 19 | |
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| 20 | ERR = zeros(size(M)); |
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| 21 | |
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| 22 | |
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| 23 | % norms is meaningless here, since we do not have ground truth |
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| 24 | % geometric data (normals) for this image. just make norms something, |
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| 25 | %so the affine_error computation does not generate an error. |
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| 26 | |
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| 27 | for i = 1:432 |
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| 28 | norms(:,i) = [1 0 0 1]'; |
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| 29 | end |
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| 30 | |
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| 31 | INC = (test2_im_data > .2); |
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| 32 | |
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| 33 | [err, aff_err, stable] = compare_affine(M,INC,3,ERR,norms,s,num_random_starts,1); |
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| 34 | |
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| 35 | |
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