[37] | 1 | % Demonstration of feature matching via simple correlation, and then using |
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| 2 | % RANSAC to estimate the fundamental matrix and at the same time identify |
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| 3 | % (mostly) inlying matches |
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| 4 | % |
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| 5 | % Usage: testfund - Demonstrates fundamental matrix calculation |
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| 6 | % on two default images |
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| 7 | % testfund(im1,im2) - Computes fundamental matrix on two supplied images |
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| 8 | % |
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| 9 | % Edit code as necessary to tweak parameters |
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| 10 | |
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| 11 | % Copyright (c) 2004-2005 Peter Kovesi |
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| 12 | % School of Computer Science & Software Engineering |
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| 13 | % The University of Western Australia |
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| 14 | % http://www.csse.uwa.edu.au/ |
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| 15 | % |
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| 16 | % Permission is hereby granted, free of charge, to any person obtaining a copy |
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| 17 | % of this software and associated documentation files (the "Software"), to deal |
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| 18 | % in the Software without restriction, subject to the following conditions: |
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| 19 | % |
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| 20 | % The above copyright notice and this permission notice shall be included in |
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| 21 | % all copies or substantial portions of the Software. |
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| 22 | % |
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| 23 | % The Software is provided "as is", without warranty of any kind. |
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| 24 | |
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| 25 | % February 2004 |
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| 26 | % August 2005 Octave compatibility |
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| 27 | |
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| 28 | function [Ftrans,correlations]=testfund(im1,im2) |
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| 29 | |
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| 30 | if nargin == 0 |
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| 31 | im1 = imread('im02.jpg'); |
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| 32 | im2 = imread('im03.jpg'); |
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| 33 | end |
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| 34 | correlations = []; |
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| 35 | v = version; Octave=0;% Crude Octave test |
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| 36 | thresh = 500; % Harris corner threshold |
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| 37 | nonmaxrad = 3; % Non-maximal suppression radius |
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| 38 | dmax = 100; % Maximum search distance for matching |
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| 39 | w = 11; % Window size for correlation matching |
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| 40 | |
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| 41 | % Find Harris corners in image1 and image2 |
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| 42 | [cim1, r1, c1] = harris(im1, 1, thresh, 3); clear cim1; |
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| 43 | show(im1,1), hold on, plot(c1,r1,'r+'); |
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| 44 | |
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| 45 | [cim2, r2, c2] = harris(im2, 1, thresh, 3); clear cim2; |
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| 46 | show(im2,2), hold on, plot(c2,r2,'r+'); |
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| 47 | drawnow |
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| 48 | |
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| 49 | correlation = 0; % Change this between 1 or 0 to switch between the two |
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| 50 | % matching functions below |
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| 51 | |
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| 52 | if correlation % Use normalised correlation matching |
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| 53 | [m1,m2] = matchbycorrelation(im1, [r1';c1'], im2, [r2';c2'], w, dmax); |
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| 54 | |
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| 55 | else % Use monogenic phase matching |
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| 56 | nscale = 1; |
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| 57 | minWaveLength = 10; |
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| 58 | mult = 4; |
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| 59 | sigmaOnf = .2; |
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| 60 | [m1,m2] = matchbymonogenicphase(im1, [r1';c1'], im2, [r2';c2'], w, dmax,... |
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| 61 | nscale, minWaveLength, mult, sigmaOnf); |
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| 62 | end |
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| 63 | |
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| 64 | % Display putative matches |
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| 65 | show(im1,3), set(3,'name','Putative matches') |
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| 66 | if Octave, figure(1); title('Putative matches'), axis('equal'), end |
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| 67 | for n = 1:length(m1); |
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| 68 | line([m1(2,n) m2(2,n)], [m1(1,n) m2(1,n)]) |
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| 69 | end |
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| 70 | |
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| 71 | % Assemble homogeneous feature coordinates for fitting of the |
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| 72 | % fundamental matrix, note that [x,y] corresponds to [col, row] |
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| 73 | x1 = [m1(2,:); m1(1,:); ones(1,length(m1))]; |
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| 74 | x2 = [m2(2,:); m2(1,:); ones(1,length(m1))]; |
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| 75 | |
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| 76 | t = .002; % Distance threshold for deciding outliers |
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| 77 | |
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| 78 | % Change the commenting on the lines below to switch between the use |
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| 79 | % of 7 or 8 point fundamental matrix solutions, or affine fundamental |
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| 80 | % matrix solution. |
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| 81 | % [F, inliers] = ransacfitfundmatrix7(x1, x2, t, 1); |
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| 82 | [F, inliers] = ransacfitfundmatrix(x1, x2, t, 1); |
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| 83 | % [F, inliers] = ransacfitaffinefund(x1, x2, t, 1); |
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| 84 | fprintf('Number of inliers was %d (%d%%) \n', ... |
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| 85 | length(inliers),round(100*length(inliers)/length(m1))) |
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| 86 | |
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| 87 | [Ftrans, transinliers] = ransacfittransfundmatrix(x1, x2, t, 1); |
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| 88 | correlations = [correlations;[m1(:,transinliers)',m2(:,transinliers)']]; |
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| 89 | [U,S,V]=svd(Ftrans); |
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| 90 | epipole=[V(2,3)/V(3,3);V(1,3)/V(3,3)] |
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| 91 | fprintf('Number of inliers was %d (%d%%) \n', ... |
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| 92 | length(inliers),round(100*length(transinliers)/length(m1))) |
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| 93 | fprintf('Number of putative matches was %d \n', length(m1)) |
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| 94 | |
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| 95 | % Display both images overlayed with inlying matched feature points |
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| 96 | |
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| 97 | if Octave |
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| 98 | figure(4); title('Inlying matches'), axis('equal'), |
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| 99 | else |
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| 100 | show(im1,4), set(4,'name','Inlying matches'), hold on |
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| 101 | end |
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| 102 | plot(m1(2,inliers),m1(1,inliers),'c+'); |
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| 103 | % plot(m2(2,inliers),m2(1,inliers),'g+'); |
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| 104 | |
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| 105 | for n = inliers |
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| 106 | line([m1(2,n) m2(2,n)], [m1(1,n) m2(1,n)],'color',[0 0 1]) |
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| 107 | end |
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| 108 | |
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| 109 | show(im2,5), set(5,'name','Inlying matches'), hold on |
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| 110 | % plot(m1(2,inliers),m1(1,inliers),'c+'); |
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| 111 | plot(m2(2,inliers),m2(1,inliers),'g+'); |
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| 112 | |
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| 113 | for n = inliers |
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| 114 | line([m1(2,n) m2(2,n)], [m1(1,n) m2(1,n)],'color',[0 0 1]) |
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| 115 | end |
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| 116 | |
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| 117 | |
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| 118 | if Octave |
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| 119 | figure(4); title('Inlying matches'), axis('equal'), |
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| 120 | else |
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| 121 | show(im1,6), set(6,'name','Translational Inlying matches'), hold on |
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| 122 | end |
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| 123 | plot(m1(2,transinliers),m1(1,transinliers),'c+'); |
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| 124 | % plot(m2(2,inliers),m2(1,inliers),'g+'); |
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| 125 | |
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| 126 | for n = transinliers |
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| 127 | line([m1(2,n) m2(2,n)], [m1(1,n) m2(1,n)],'color',[0 0 1]) |
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| 128 | end |
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| 129 | |
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| 130 | show(im2,7), set(7,'name','translational Inlying matches'), hold on |
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| 131 | % plot(m1(2,inliers),m1(1,inliers),'c+'); |
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| 132 | plot(m2(2,transinliers),m2(1,transinliers),'g+'); |
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| 133 | |
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| 134 | for n = transinliers |
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| 135 | line([m1(2,n) m2(2,n)], [m1(1,n) m2(1,n)],'color',[0 0 1]) |
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| 136 | end |
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| 137 | |
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| 138 | % determine which picture is closer to the epipole |
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| 139 | p1 = [r1(transinliers)-epipole(1),c1(transinliers)-epipole(2)]'; |
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| 140 | p2 = [r2(transinliers)-epipole(1),c2(transinliers)-epipole(2)]'; |
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| 141 | dist1 = sum((sum(p1.^2)).^.5); |
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| 142 | dist2 = sum((sum(p2.^2)).^.5); |
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| 143 | cImage = (dist1>dist2)+1; |
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| 144 | |
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| 145 | DualMatches=guide([r1,c1]', [r2,c2]', epipole, 17, .85, .2,150,cImage,im1,im2 ); |
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| 146 | % correlations = [correlations;[r1(DualMatches(:,1)),c1(DualMatches(:,1)),r2(DualMatches(:,2)),c2(DualMatches(:,2))]]; |
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| 147 | correlations = [r1(DualMatches(:,1)),c1(DualMatches(:,1)),r2(DualMatches(:,2)),c2(DualMatches(:,2))]; |
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| 148 | fprintf('Number of guided matches was %d \n', size(DualMatches,1)) |
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| 149 | |
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| 150 | show(im1,9), set(9,'name','Dual matches'), hold on |
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| 151 | plot(c1(DualMatches(:,1)),r1(DualMatches(:,1)),'g+'); |
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| 152 | % plot(c2(DualMatches(:,2)),r2(DualMatches(:,2)),'g+'); |
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| 153 | |
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| 154 | %plot(epipole(2),epipole(1),'r*'); |
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| 155 | for n = 1:1:size(DualMatches,1) |
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| 156 | line([c1(DualMatches(n,1)) c2(DualMatches(n,2))], [r1(DualMatches(n,1)) r2(DualMatches(n,2))],'color',[0 0 1]) |
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| 157 | end |
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| 158 | |
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| 159 | show(im2,8), set(8,'name','Dual matches'), hold on |
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| 160 | % plot(c1(DualMatches(:,1)),r1(DualMatches(:,1)),'c+'); |
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| 161 | plot(c2(DualMatches(:,2)),r2(DualMatches(:,2)),'g+'); |
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| 162 | |
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| 163 | %plot(epipole(2),epipole(1),'r*'); |
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| 164 | for n = 1:1:size(DualMatches,1) |
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| 165 | line([c1(DualMatches(n,1)) c2(DualMatches(n,2))], [r1(DualMatches(n,1)) r2(DualMatches(n,2))],'color',[0 0 1]) |
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| 166 | end |
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| 167 | |
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| 168 | show(im1,11), set(11,'name','All matches'), hold on |
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| 169 | plot(correlations(:,2),correlations(:,1),'g+'); |
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| 170 | % plot(c2(DualMatches(:,2)),r2(DualMatches(:,2)),'g+'); |
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| 171 | |
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| 172 | %plot(epipole(2),epipole(1),'r*'); |
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| 173 | for n = 1:1:size(correlations,1) |
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| 174 | line([correlations(n,2) correlations(n,4)], [correlations(n,1) correlations(n,3)],'color',[0 0 1]) |
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| 175 | end |
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| 176 | |
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| 177 | show(im2,10), set(10,'name','All matches'), hold on |
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| 178 | % plot(c1(DualMatches(:,1)),r1(DualMatches(:,1)),'c+'); |
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| 179 | plot(correlations(:,4),correlations(:,3),'g+'); |
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| 180 | |
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| 181 | %plot(epipole(2),epipole(1),'r*'); |
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| 182 | for n = 1:1:size(correlations,1) |
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| 183 | line([correlations(n,2) correlations(n,4)], [correlations(n,1) correlations(n,3)],'color',[0 0 1]) |
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| 184 | end |
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| 185 | n |
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