source: proiecte/pmake3d/make3d_original/Make3dSingleImageStanford_version0.1/third_party/zisserman/vgg_examples/testhomog_vgg.m @ 37

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1% Demonstration of feature matching via simple correlation, and then using
2% RANSAC to estimate the homography matrix and at the same time identify
3% (mostly) inlying matches
4
5% Peter Kovesi 
6% School of Computer Science & Software Engineering
7% The University of Western Australia
8% pk at csse uwa edu au
9% http://www.csse.uwa.edu.au/~pk
10%
11% February 2004
12
13% Adapted to use vgg functions by Peter Kovesi and Andrew Zisserman
14
15function H = testhomog_vgg
16
17    close all   
18   
19    thresh = 500;   % Harris corner threshold
20    nonmaxrad = 3;  % Non-maximal suppression radius
21    dmax = 100;
22    w = 11;    % Window size for correlation matching
23   
24    im1 = rgb2gray(imread('keble.000.png'));
25    im2 = rgb2gray(imread('keble.003.png'));
26
27    % Find Harris corners in image1 and image2
28    [cim1, r1, c1] = harris(im1, 1, thresh, 3);
29    show(im1,1), hold on, plot(c1,r1,'r+');
30
31    [cim2, r2, c2] = harris(im2, 1, thresh, 3);
32    show(im2,2), hold on, plot(c2,r2,'r+');
33
34    drawnow
35
36tic
37    [m1,m2] = matchbycorrelation(im1, [r1';c1'], im2, [r2';c2'], w, dmax);
38toc
39    % Display putative matches
40    show(im1,3), set(3,'name','Putative matches'), hold on   
41    for n = 1:length(m1);
42        line([m1(2,n) m2(2,n)], [m1(1,n) m2(1,n)])
43    end
44
45    % Assemble homogeneous feature coordinates for fitting of the
46    % homography matrix, note that [x,y] corresponds to [col, row]
47    x1 = [m1(2,:); m1(1,:); ones(1,length(m1))];
48    x2 = [m2(2,:); m2(1,:); ones(1,length(m1))];   
49   
50    t = .001;  % Distance threshold for deciding outliers
51    [H, inliers] = ransacfithomography_vgg(x1, x2, t);
52
53    fprintf('Number of inliers was %d (%d%%) \n', ...
54            length(inliers),round(100*length(inliers)/length(m1)))
55    fprintf('Number of putative matches was %d \n', length(m1))       
56   
57    % Display both images overlayed with inlying matched feature points
58    show(double(im1)+double(im2),4), set(4,'name','Inlying matches'), hold on
59    plot(m1(2,inliers),m1(1,inliers),'r+');
60    plot(m2(2,inliers),m2(1,inliers),'g+');   
61
62    % Step through each matched pair of points and display the
63    % line linking the points on the overlayed images.
64
65    for n = inliers
66        line([m1(2,n) m2(2,n)], [m1(1,n) m2(1,n)],'color',[0 0 1])
67    end
68   
69    return
70   
71   
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