i am trying to execute the below source code multiple 2d image to reconstruct single 3d image , but i have err on that could pls recover this coding err

clc;
disp('SFMedu: Structrue From Motion for Education Purpose');
disp('Version 2 @ 2014');
disp('Written by Jianxiong Xiao (MIT License)');

%%set up things
clear;
close all;
addpath(genpath('matchSIFT'));
addpath(genpath('denseMatch'));
addpath(genpath('RtToolbox'));

visualize = false;

%%data

frames.images{1}='images/B21.jpg';
frames.images{2}='images/B22.jpg';
frames.images{3}='images/B23.jpg';
frames.images{4}='images/B24.jpg';
frames.images{5}='images/B25.jpg';

%{
frames.images{1}='images/kermit000.jpg';
frames.images{2}='images/kermit001.jpg';
frames.images{3}='images/kermit002.jpg';
%}

%{
frames.images{1} ='/Users/xj/Dropbox/Camera Uploads/2014-09-03 14.15.54.jpg';
frames.images{2} ='/Users/xj/Dropbox/Camera Uploads/2014-09-03 14.15.59.jpg';
frames.images{3} ='/Users/xj/Dropbox/Camera Uploads/2014-09-03 14.16.02.jpg';
frames.images{4} ='/Users/xj/Dropbox/Camera Uploads/2014-09-03 14.16.05.jpg';
frames.images{5} ='/Users/xj/Dropbox/Camera Uploads/2014-09-03 14.16.09.jpg';
frames.images{6} ='/Users/xj/Dropbox/Camera Uploads/2014-09-03 14.16.16.jpg';
frames.images{7} ='/Users/xj/Dropbox/Camera Uploads/2014-09-03 14.16.20.jpg';
frames.images{8} ='/Users/xj/Dropbox/Camera Uploads/2014-09-03 14.16.23.jpg';
frames.images{9} ='/Users/xj/Dropbox/Camera Uploads/2014-09-03 14.16.26.jpg';
frames.images{10}='/Users/xj/Dropbox/Camera Uploads/2014-09-03 14.16.29.jpg';
frames.images{11}='/Users/xj/Dropbox/Camera Uploads/2014-09-03 14.16.33.jpg';
frames.images{12}='/Users/xj/Dropbox/Camera Uploads/2014-09-03 14.16.36.jpg';
%}

%%data 
frames.length = length(frames.images);

try
    frames.focal_length = extractFocalFromEXIF(frames.images{1});
catch
end
if ~isfield(frames,'focal_length') || isempty(frames.focal_length)
    fprintf('Warning: cannot find the focal length from the EXIF\n');
    frames.focal_length = 719.5459; % for testing with the B??.jpg sequences
end

maxSize = 1024;
frames.imsize = size(imread(frames.images{1}));
if max(frames.imsize)>maxSize
    scale = maxSize/max(frames.imsize);
    frames.focal_length = frames.focal_length * scale;
    frames.imsize = size(imresize(imread(frames.images{1}),scale));
end

frames.K = f2K(frames.focal_length);
disp('intrinsics:');
disp(frames.K);

%%SIFT matching and Fundamental Matrix Estimation
for frame=1:frames.length-1    
    % need to set this random seed to produce exact same result
    s = RandStream('mcg16807','Seed',10); 
    RandStream.setGlobalStream(s);

      % keypoint matching
      %pair = match2viewSURF(frames, frame, frame+1);
      pair = match2viewSIFT(frames, frame, frame+1);

      if visualize, showMatches(pair,frames); title('raw feature matching'); end

      if true % choose between different ways of getting E
          % Estimate Fundamental matrix
          pair = estimateF(pair);    
          % Convert Fundamental Matrix to Essential Matrix
          pair.E = frames.K' * pair.F * frames.K; % MVG Page 257 Equation 9.12
      else
          % Estimate Essential Matrix directly using 5-point algorithm
          pair = estimateE(pair,frames); 
      end

      if visualize, showMatches(pair,frames); title('inliers'); end

      % Get Poses from Essential Matrix
      pair.Rt = RtFromE(pair,frames);

      % Convert the pair into the BA format
      Graph{frame} = pair2graph(pair,frames);

      % re-triangulation
      Graph{frame} = triangulate(Graph{frame},frames);
      if visualize, visualizeGraph(Graph{frame},frames); title('triangulation'); end

      % outlier rejection
      % Graph{frame} = removeOutlierPts(Graph{frame});

      % bundle adjustment
      Graph{frame} = bundleAdjustment(Graph{frame});
      if visualize, visualizeGraph(Graph{frame},frames); title('after two-view bundle adjustment'); end
  end

%%merge the graphs
%close all
fprintf('\n\nmerging graphs....\n');

mergedGraph = Graph{1};

for frame=2:frames.length-1
    % merge graph
    mergedGraph = merge2graphs(mergedGraph,Graph{frame});

      % re-triangulation
      mergedGraph = triangulate(mergedGraph,frames);
      if visualize, visualizeGraph(mergedGraph,frames); title('triangulation'); end

      % outlier rejection
      % mergedGraph = removeOutlierPts(mergedGraph,10);

      % bundle adjustment
      mergedGraph = bundleAdjustment(mergedGraph);

      % outlier rejection
      mergedGraph = removeOutlierPts(mergedGraph, 10);

      % bundle adjustment
      mergedGraph = bundleAdjustment(mergedGraph);    

      if visualize, visualizeGraph(mergedGraph,frames); title('after bundle adjustment'); end
  end

%{
% outlier rejection
mergedGraph = removeOutlierPts(mergedGraph);

% bundle adjustment
mergedGraph = bundleAdjustment(mergedGraph);
if visualize, visualizeGraph(mergedGraph,frames); title('after bundle adjustment'); end

% bundle adjustment with focal length changes
mergedGraph = bundleAdjustment(mergedGraph,true);
if visualize, visualizeGraph(mergedGraph,frames); title('after bundle adjustment with focal length'); end
%}

%printReprojectionError(mergedGraph); % [for homework]

%visualizeReprojection(mergedGraph,frames); % [for homework]

points2ply('sparse.ply',mergedGraph.Str);

if frames.focal_length ~= mergedGraph.f
    disp('Focal length is adjusted by bundle adjustment');
    frames.focal_length = mergedGraph.f;
    frames.K = f2K(frames.focal_length);
    disp(frames.K);
end

%%dense matching

fprintf('dense matching ...\n');
for frame=1:frames.length-1
    Graph{frame} = denseMatch(Graph{frame}, frames, frame, frame+1);
end

%%dense reconstruction
fprintf('triangulating dense points ...\n');
for frame=1:frames.length-1
    clear X;
    P{1} = frames.K * mergedGraph.Mot(:,:,frame);
    P{2} = frames.K * mergedGraph.Mot(:,:,frame+1);
    %par
    for j=1:size(Graph{frame}.denseMatch,2)
        X(:,j) = vgg_X_from_xP_nonlin(reshape(Graph{frame}.denseMatch(1:4,j),2,2),P,repmat([frames.imsize(2);frames.imsize(1)],1,2));
    end
    X = X(1:3,:) ./ X([4 4 4],:);
    x1= P{1} * [X; ones(1,size(X,2))];
    x2= P{2} * [X; ones(1,size(X,2))];
    x1 = x1(1:2,:) ./ x1([3 3],:);
    x2 = x2(1:2,:) ./ x2([3 3],:);
    Graph{frame}.denseX = X;
    Graph{frame}.denseRepError = sum(([x1; x2] - Graph{frame}.denseMatch(1:4,:)).^2,1);

      Rt1 = mergedGraph.Mot(:, :, frame);
      Rt2 = mergedGraph.Mot(:, :, frame+1);
      C1 = - Rt1(1:3, 1:3)' * Rt1(:, 4);
      C2 = - Rt2(1:3, 1:3)' * Rt2(:, 4);
      view_dirs_1 = bsxfun(@minus, X, C1);
      view_dirs_2 = bsxfun(@minus, X, C2);
      view_dirs_1 = bsxfun(@times, view_dirs_1, 1 ./ sqrt(sum(view_dirs_1 .* view_dirs_1)));
      view_dirs_2 = bsxfun(@times, view_dirs_2, 1 ./ sqrt(sum(view_dirs_2 .* view_dirs_2)));
      Graph{frame}.cos_angles = sum(view_dirs_1 .* view_dirs_2);

      c_dir1 = Rt1(3, 1:3)';
      c_dir2 = Rt2(3, 1:3)';
      Graph{frame}.visible = (sum(bsxfun(@times, view_dirs_1, c_dir1)) > 0) & (sum(bsxfun(@times, view_dirs_2, c_dir2)) > 0);
  end

% visualize the dense point cloud
if visualize
    figure
    for frame=1:frames.length-1
        hold on
        goodPoint =  Graph{frame}.denseRepError < 0.05;
        plot3(Graph{frame}.denseX(1,goodPoint),Graph{frame}.denseX(2,goodPoint),Graph{frame}.denseX(3,goodPoint),'.b','Markersize',1);
    end
    hold on
    plot3(mergedGraph.Str(1,:),mergedGraph.Str(2,:),mergedGraph.Str(3,:),'.r')
    axis equal
    title('dense cloud')
    for i=1:frames.length
        drawCamera(mergedGraph.Mot(:,:,i), frames.imsize(2), frames.imsize(1), frames.K(1,1), 0.001,i*2-1);
    end
    axis tight
end

% output as ply file to open in Meshlab (Open Software available at http://meshlab.sourceforge.net )
plyPoint = [];
plyColor = [];
for frame=1:frames.length-1
    goodPoint =  (Graph{frame}.denseRepError < 0.05) & (Graph{frame}.cos_angles < cos(5 / 180 * pi)) & Graph{frame}.visible;
    X = Graph{frame}.denseX(:,goodPoint);
    % get the color of the point
    P{1} = frames.K * mergedGraph.Mot(:,:,frame);
    x1= P{1} * [X; ones(1,size(X,2))];
    x1 = round(x1(1:2,:) ./ x1([3 3],:));
    x1(1,:) = frames.imsize(2)/2 - x1(1,:);
    x1(2,:) = frames.imsize(1)/2 - x1(2,:);
    indlin = sub2ind(frames.imsize(1:2),x1(2,:),x1(1,:));
    im = imresize(imread(frames.images{frame}),frames.imsize(1:2));
    imR = im(:,:,1);
    imG = im(:,:,2);
    imB = im(:,:,3);
    colorR = imR(indlin);
    colorG = imG(indlin);
    colorB = imB(indlin);
    plyPoint = [plyPoint X];
    plyColor = [plyColor [colorR; colorG; colorB]];
end

points2ply('dense.ply',plyPoint,plyColor);

[KSSV]

What error? Which line?

[Mano R]

sir actually this is net source code from http://3dvision.princeton.edu/courses/SFMedu/ and i executing this source code i has a err like

Error in denseMatch (line 31)
match_pair= propagate(initial_match, [], [], matchable_image1, matchable_image2, zncc1, zncc2, HalfSizePropagate );

[Mano R]

sir please help me to recover this error.

[KSSV]

Specify the error...you said line umber of error...what error it thorws?

[Mano R]

sir actually i am very new to matlab, so i can't find what is the actual mistake on that coding.. Attempt to execute SCRIPT pq_create as a function: E:\SFMedu2\SFMedu2\denseMatch\priority_queue_1.0\pq_create.m

Error in propagate (line 29) match_heap = pq_create(NbMaxStartMatch*25+MaxIndexValidMatch);

Error in denseMatch (line 31) match_pair= propagate(initial_match, [], [], matchable_image1, matchable_image2, zncc1, zncc2, HalfSizePropagate );

Error in SFMedu2 (line 178) Graph{frame} = denseMatch(Graph{frame}, frames, frame, frame+1);

Answer 1

[Walter Roberson]

You need to compile pq_create for your platform. It is provided ad source code mex files it appears.

[Mano R]

sir, when i am trying to compile pq_create on my platform its shows an error like"No supported compiler or SDK was found. For options, visit http://www.mathworks.com/support/compilers/R2014a/win32." what i do?

[Walter Roberson]

What you need to do is install Microsoft Windows SDK 7.1

Note: if you are using Windows 10, it might be difficult to install SDK 7.1