genDescriptors.m

function [ final_out ] = genDescriptors(img1_path, img2_path, label, path)
%{
    Author : Vaibhav Malpani 
    Face Verification using SIFT features in SVM classifier

    Generates SIFT features corresponding to (x,y) coordinates mentioned 
    in x_all and y_all.
    
    Parameters:
    img1_path - filename/filename.jpg
    img2_path - filename/filename.jpg
    path - path of the dataset (append img1_path or img2_path to get file)
    label - class label for each pair
    final_out(1) - matrix with the first column corresponding to the class label
    final_out(2:end) - features generated by SIFT
%}

    % points of interest
    x_all = [90, 101,116, 140,150,160, 99,103,115, 142,148,158, 126,114,124,138, 108,126,127,145, 122,130, 108,160,180, 105,127,148, 113,140];
    y_all = [107,105,106, 108,106,107, 115,113,115, 113,114,115, 117,142,140,141, 162,160,165,161, 182,52, 60,54,70, 152,145,150, 175,184];

    % window size
%     siftsize = 32;
    siftsize = 24;
    scale_sift(1:size(x_all,2)) = siftsize/12;    
    
    full_file_path1 = strcat(path,'/',img1_path);
    full_file_path2 = strcat(path,'/',img2_path);
    
    % generate SIFT features for im1
    [im1, map1] = imread(full_file_path1);
    img1 = single(im1)./ 255;
    frames = [x_all; y_all; scale_sift; zeros(1,size(x_all,2))];
    [f1_img1, d1_img1] = vl_sift(img1, 'frames', frames);
    
    % generate SIFT features for im2
    [im2, map2] = imread(full_file_path2);
    img2 = single(im2)./ 255;
    [f1_img2, d1_img2] = vl_sift(img2, 'frames', frames);
    
    % generate pairwise descriptors
    pair_descriptor = d1_img1(:) - d1_img2(:); 
    final_out = [label pair_descriptor'];
end