facepos.m

eye detection sample in matlab. Eyetrackers can analyze a driver’s level of attentiveness while driv

function [facepos,sample] = facepos(pic,binpic)
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% INPUTS:
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% pic - a grayscale image with values between 0 and 255
% binpic - a binary matrix indicating the location of skin tones in the pic matrix
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% OUTPUTS:
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% facepos - a position vector [y x score] of all found faces
% sample - the higest score sample (a 360 value vecotr, to view the sample
%   use display360(sample) )



    if (exist('binpic','var')==0)
        binpic = zeros(size(pic));
        binpic(1:2:size(pic,1),1:2:size(pic,2))=1;
    end
    facepos = [];
    load FC;
    test = [];
    %scale = 0.5;
    %facemap = zeros(20,20);
    
    %facemap(index360)=1;
    % picmap = filter2(facemap,binpic,'valid');
    %[y,x] = find(picmap>360);

    pic = uint8(pic);
    pic1 = pic;
    [m,n]=size(pic);
    curr_line=1;
    facepos=[];
    facepos=double(facepos);
    sample=[];
    while (curr_line<(m-19))
        tic
        mini=curr_line;
        maxi=min(curr_line+100,m);
        pic = pic1(mini:maxi,1:n);
        searchpos = binpic(mini:maxi,1:n);
        [test,y,x] = fdprep(pic,uint8(searchpos));
        test = double(test);
        toc
        c= clock;
        [l,sc] = osuSVMclass(test,FC.n, FC.alpha, FC.sv,FC.b, FC.params);
        fprintf('SVM elapsed time: %f', etime(clock,c));
        ind= find(l==1);
        addme=ones(size(y));
        addme=addme.*curr_line;
        y=double(y);
        y=y+addme;
        x = double(x);
        facepos = [facepos;y(ind)', x(ind)',sc(ind)'];
        sample = [sample, test(:,ind)];
        curr_line=curr_line+80;
    end