Can I get a descriptor SURF of each point of image

Question

as indicated in the title, I'm looking to get a Descriptor-SURF for each image point I do not want the interests of points, but the SURF descriptor on each point of the image. The SURF descriptor use an integral image to compute the descriptors

% Create Integral Image
iimg=IntegralImage_IntegralImage(img);

then an extraction of the interest points

FastHessianData.thresh = Options.tresh;
FastHessianData.octaves = Options.octaves;
FastHessianData.init_sample = Options.init_sample;
FastHessianData.img = iimg;
ipts = FastHessian_getIpoints(FastHessianData,Options.verbose)
% Describe the interest points
if(~isempty(ipts))
    ipts = SurfDescriptor_DecribeInterestPoints(ipts,Options.upright, Options.extended, iimg, Options.verbose);
end

the function with which the points are got

function ipts=FastHessian_getIpoints(FastHessianData,verbose)
% filter index map

filter_map = [0,1,2,3;
    1,3,4,5;
    3,5,6,7;
    5,7,8,9;
    7,9,10,11]+1;

np=0; ipts=struct;

% Build the response map
responseMap=FastHessian_buildResponseMap(FastHessianData);

% Find the maxima acrros scale and space
for o = 1:FastHessianData.octaves
    for i = 1:2
        b = responseMap{filter_map(o,i)};
        m = responseMap{filter_map(o,i+1)};
        t = responseMap{filter_map(o,i+2)};

        % loop over middle response layer at density of the most
        % sparse layer (always top), to find maxima across scale and space
        [c,r]=ndgrid(0:t.width-1,0:t.height-1);
        r=r(:); c=c(:);

        p=find(FastHessian_isExtremum(r, c, t, m, b,FastHessianData));
        for j=1:length(p);
            ind=p(j);
            [ipts,np]=FastHessian_interpolateExtremum(r(ind), c(ind), t, m, b, ipts,np);
        end
    end
end

% Show laplacian and response maps with found interest-points
if(verbose)
    % Show the response map
    if(verbose)
        fig_h=ceil(length(responseMap)/3);
        h=figure;  set(h,'name','Laplacian');
        for i=1:length(responseMap), 
            pic=reshape(responseMap{i}.laplacian,[responseMap{i}.width responseMap{i}.height]);
            subplot(3,fig_h,i); imshow(pic,[]); hold on;
        end
        h=figure; set(h,'name','Responses');
        h_res=zeros(1,length(responseMap));
        for i=1:length(responseMap), 
            pic=reshape(responseMap{i}.responses,[responseMap{i}.width responseMap{i}.height]);
            h_res(i)=subplot(3,fig_h,i); imshow(pic,[]); hold on;
        end
    end

    % Show the maximum points
    disp(['Number of interest points found ' num2str(np)]);
    scales=zeros(1,length(responseMap));
    scaley=zeros(1,length(responseMap));
    scalex=zeros(1,length(responseMap));
    for i=1:length(responseMap)
        scales(i)=responseMap{i}.filter*(2/15);
        scalex(i)=responseMap{i}.width/size(FastHessianData.img,2);
        scaley(i)=responseMap{i}.height/size(FastHessianData.img,1);
    end
    for i=1:np
        [t,ind]=min((scales-ipts(i).scale).^2);
        plot(h_res(ind),ipts(i).y*scaley(ind)+1,ipts(i).x*scalex(ind)+1,'o','color',rand(1,3));
    end
end

how to keep all the points without doning this step of detection, then describe all of this points by the SURF descriptor.

Answer 1

In your code you have clearly the detector and descriptor functions separated:

• FastHessian_getIpoints returns the list of interesting keypoints
• SurfDescriptor_DecribeInterestPoints computes the SURF descriptor for the given points.

Just get rid of your detector and call the descriptor function providing as an input ALL points in the image.

So variable ipts will contain ALL points instead of only those returned by the keypoint detector