非常感谢P. Felzenszwalb开源了dpm的代码，也同样感谢opencv实现了C++版本的dpm检测部分。但这里需要将matllab训练出来的*.mat模型转换成opencv下可以使用的.xml模型，转换代码如下：
function MAT2XMLmodel_401(matmodel,xmlfile)
matmodel = 'sofa_final';
xmlfile = 'sofa_final.xml';
load(matmodel);
fid = fopen(xmlfile,'w');
fprintf(fid,'<Model>\n');
ncom = length(model.rules{model.start});
fprintf(fid,'\t<!-- Number of components -->\n');
fprintf(fid,'\t<NumComponents>%d</NumComponents>\n',ncom);
nfeature = 31;
fprintf(fid,'\t<!-- Number of features -->\n');
fprintf(fid,'\t<P>%d</P>\n',nfeature);
fprintf(fid,'\t<!-- score threshold -->\n');
fprintf(fid,'\t<scoreThreshold>%.16f</scoreThreshold>\n',model.thresh);
layer = 1;
for icom = 1:ncom
fprintf(fid,'\t<Component>\n');
fprintf(fid,'\t\t<!-- Root filter description -->\n');
fprintf(fid,'\t\t<RootFilter>\n');
% attention: X,Y swap
rhs = model.rules{model.start}(icom).rhs;
% assume the root filter is first on the rhs of the start rules
if model.symbols(rhs(1)).type == 'T'
% handle case where there's no deformation model for the root
root = model.symbols(rhs(1)).filter;
else
% handle case where there is a deformation model for the root
root = model.symbols(model.rules{rhs(1)}(layer).rhs).filter;
end
filternum = root;
sizeX = model.filters(filternum).size(2);
sizeY = model.filters(filternum).size(1);
fprintf(fid,'\t\t\t<!-- Dimensions -->\n');
fprintf(fid,'\t\t\t<sizeX>%d</sizeX>\n',sizeX);
fprintf(fid,'\t\t\t<sizeY>%d</sizeY>\n',sizeY);
fprintf(fid,'\t\t\t<!-- Weights (binary representation) -->\n');
fprintf(fid,'\t\t\t<Weights>');
for iY = 1:sizeY
for iX = 1:sizeX
% original mat has 32 which is larger than nfeature=31 by 1
fwrite(fid,model.filters(filternum).w(iY,iX,1:nfeature),'double'); % need verify
end
end
fprintf(fid,'\t\t\t</Weights>\n');
fprintf(fid,'\t\t\t<!-- Linear term in score function -->\n');
fprintf(fid,'\t\t\t<LinearTerm>%.16f</LinearTerm>\n',... % need verify
model.rules{model.start}(icom).offset.w);
fprintf(fid,'\t\t</RootFilter>\n');
fprintf(fid,'\t\t<!-- Part filters description -->\n');
fprintf(fid,'\t\t<PartFilters>\n');
npart = length(model.rules{model.start}(icom).rhs) -1 ;
fprintf(fid,'\t\t\t<NumPartFilters>%d</NumPartFilters>\n',npart);
for ipart = 2: npart+1
fprintf(fid,'\t\t\t<!-- Part filter ? description -->\n');
fprintf(fid,'\t\t\t<PartFilter>\n');
irule = model.rules{model.start}(icom).rhs(ipart);
filternum = model.symbols(model.rules{irule}.rhs).filter;
sizeX = model.filters(filternum).size(2);
sizeY = model.filters(filternum).size(1);
fprintf(fid,'\t\t\t\t<sizeX>%d</sizeX>\n',sizeX);
fprintf(fid,'\t\t\t\t<sizeY>%d</sizeY>\n',sizeY);
fprintf(fid,'\t\t\t\t<!-- Weights (binary representation) -->\n');
fprintf(fid,'\t\t\t\t<Weights>');
for iY = 1:sizeY
for iX = 1:sizeX
% original mat has 32 which is larger than nfeature=31 by 1
fwrite(fid,'\t\t\t\t</Weights>\n');
fprintf(fid,'\t\t\t\t<!-- Part filter offset -->\n');
fprintf(fid,'\t\t\t\t<V>\n');
fprintf(fid,'\t\t\t\t\t<Vx>%d</Vx>\n',model.rules{model.start}(icom).anchor{ipart}(1)+1); %[dx,dy,ds]
fprintf(fid,'\t\t\t\t\t<Vy>%d</Vy>\n',model.rules{model.start}(icom).anchor{ipart}(2)+1);
fprintf(fid,'\t\t\t\t</V>\n');
fprintf(fid,'\t\t\t\t<!-- Quadratic penalty function coefficients -->\n');
fprintf(fid,'\t\t\t\t<Penalty>\n');
fprintf(fid,'\t\t\t\t\t<dx>%.16f</dx>\n',model.rules{irule}.def.w(2));
fprintf(fid,'\t\t\t\t\t<dy>%.16f</dy>\n',model.rules{irule}.def.w(4));
fprintf(fid,'\t\t\t\t\t<dxx>%.16f</dxx>\n',model.rules{irule}.def.w(1));
fprintf(fid,'\t\t\t\t\t<dyy>%.16f</dyy>\n',model.rules{irule}.def.w(3));
fprintf(fid,'\t\t\t\t</Penalty>\n');
fprintf(fid,'\t\t\t</PartFilter>\n');
end
fprintf(fid,'\t\t</PartFilters>\n');
fprintf(fid,'\t</Component>\n');
end
fprintf(fid,'</Model>\n');
fclose(fid);
end
