final commit

computeLearnedSIFT.m

@@ -1,13 +1,10 @@
 function [locs,desc] = computeLearnedSIFT(im, GaussianPyramid, locsDoG, k, levels)
 [R,C,L] = size(GaussianPyramid);
-patchWidth = 9;
 locs = zeros(0,3);
-norm_patch_size = 64;
 patches=zeros(1,64,64);
 for i=1:size(locsDoG,1)
-    level = find(levels==locsDoG(i,3));
-    patch_half_size = floor(8*k^(1+levels(level)-levels(1)));
-    bound = floor(sqrt(2)*patch_half_size);
+    %bound = floor(sqrt(2)*patch_half_size);
+    bound=32;
     if locsDoG(i,1)>=bound && locsDoG(i,2)>=bound && locsDoG(i,1)<=C-bound && locsDoG(i,2)<=R-bound
         locs = [locs;locsDoG(i,:)];
         % compute 128-D discriptor

siftMatch.m

@@ -7,7 +7,7 @@
 %									into desc1 and the second column are indices into desc2
 
 if nargin<3
-    ratio = .8;
+    ratio = .6;
 end
 
 % compute the pairwise Hamming distance
@@ -16,8 +16,8 @@
 
 % suprress match between descriptors that are not distriminative.
 r = D(1,:)./D(2,:); 
-ix = ix(r < ratio | isnan(r)); 
-I2 = I(1,r < ratio | isnan(r));
+ix = ix((r < ratio)& D(1,:)<2 | isnan(r)); 
+I2 = I(1,(r < ratio)& D(1,:)<2 | isnan(r));
 
 %output
 matches = [ix' I2'];

siftMatch.m~

@@ -0,0 +1,26 @@
+function [matches] = siftMatch(desc1, desc2, ratio)
+%function [matches] = briefMatch(desc1, desc2, ratio)
+% Performs the descriptor matching
+% inputs  : desc1 , desc2 - m1 x n and m2 x n matrix. m1 and m2 are the number of keypoints in image 1 and 2.
+%						    n is the number of bits in the brief
+% outputs : matches - p x 2 matrix. where the first column are indices
+%									into desc1 and the second column are indices into desc2
+
+if nargin<3
+    ratio = .7;
+end
+
+% compute the pairwise Hamming distance
+[D,I] = pdist2(desc2,desc1,'cityblock','Smallest',2);
+ix = 1:size(desc1,1);
+
+% suprress match between descriptors that are not distriminative.
+r = D(1,:)./D(2,:); 
+ix = ix((r < ratio)& D(1,:)<2 | isnan(r)); 
+I2 = I(1,(r < ratio)& D(1,:)<2| isnan(r));
+
+%output
+matches = [ix' I2'];
+
+
+end

testMatch.m

@@ -6,19 +6,17 @@
 % im1 = imread('../data/pf_scan_scaled.jpg');
 im1 = im2double(im1);
 if size(im1,3)==3
-    im1= rgb2gray(im1);
+    im1_gray= rgb2gray(im1);
 end
-[locs1, desc1] = learned_siftLite(im1);
+[locs1, desc1] = learned_siftLite(im1_gray);
 
 %im2 = imread('../data/chickenbroth_01.jpg');
 im2 = imrotate(im1,20);
+im2_gray=imrotate(im1_gray,20);
 % im2 = imread('../data/incline_R.png');
 % im2 = imread('../data/pf_stand.jpg');
 im2 = im2double(im2);
-if size(im2,3)==3
-    im2= rgb2gray(im2);
-end
-[locs2, desc2] = learned_siftLite(im2);
+[locs2, desc2] = learned_siftLite(im2_gray);
 
 [matches] = siftMatch(desc1, desc2);
-plotMatches(im1, im2, matches, locs1, locs2)
+img=getNewImg(im1, im2, matches, locs1, locs2);