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1 | function F = u2Fdlt(u,do_norm) |
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2 | % u2Fdlt linear estimation of the Fundamental matrix |
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3 | % from point correspondences |
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4 | % |
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5 | % H = u2Fdlt(u,{do_norm=1}) |
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6 | % u ... {4|6}xN corresponding coordinates |
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7 | % do_norm .. do isotropic normalization of points? |
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8 | % |
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9 | % F ... 3x3 fundamental matrix |
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10 | % |
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11 | % $Id: u2Fdlt.m,v 1.1 2005/05/23 16:16:01 svoboda Exp $ |
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12 | |
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13 | NoPoints = size(u,2); |
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14 | |
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15 | if nargin < 2 |
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16 | do_norm=1; |
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17 | end |
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18 | |
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19 | u = u'; |
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20 | |
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21 | % parse the input parameters |
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22 | if NoPoints<8 |
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23 | error('Too few correspondences') |
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24 | end |
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25 | |
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26 | if size(u,2) == 4, |
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27 | % make the homogenous coordinates |
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28 | u = [u(:,1:2), ones(size(u(:,1))), u(:,3:4), ones(size(u(:,1)))]; |
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29 | end |
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30 | |
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31 | u1 = u(:,1:3); |
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32 | u2 = u(:,4:6); |
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33 | |
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34 | if do_norm |
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35 | [u1,T1] = pointnormiso(u1'); |
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36 | u1 = u1'; |
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37 | [u2,T2] = pointnormiso(u2'); |
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38 | u2 = u2'; |
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39 | end |
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40 | |
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41 | % create the data matrix |
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42 | A = zeros(NoPoints,9); |
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43 | for i=1:NoPoints % create equations |
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44 | for j=1:3 |
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45 | for k=1:3 |
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46 | A(i,(j-1)*3+k)=u2(i,j)*u1(i,k); |
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47 | end |
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48 | end |
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49 | end |
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50 | |
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51 | [U,S,V] = svd(A); |
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52 | f = V(:,size(V,2)); |
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53 | F = reshape(f,3,3)'; |
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54 | |
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55 | if do_norm |
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56 | F = inv(T2)*F*T1; |
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57 | end |
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58 | |
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59 | return; |
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