我可以得到每个图像点的描述符 SURF

Question

如标题所示，我希望为每个图像点获取一个 Descriptor-SURF，我不想要点的兴趣，而是图像每个点上的 SURF 描述符。 SURF 描述符使用积分图像来计算描述符

% Create Integral Image
iimg=IntegralImage_IntegralImage(img);

然后是兴趣点的提取

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

获取点的函数

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

如何在不做这一步检测的情况下保留所有点，然后用SURF描述符描述所有这些点。

Answer 1

在您的代码中，您清楚地将检测器和描述符功能分开：

• FastHessian_getIpoints 返回有趣的关键点列表
• SurfDescriptor_DecribeInterestPoints 计算给定点的 SURF 描述符。

只需摆脱您的检测器并调用提供图像中所有点作为输入的描述符函数。

所以变量ipts 将包含所有点，而不仅仅是关键点检测器返回的点