clc; clear all;close all;clf reset; %% %%%%%%%%%%%%%%%%%%%%%%%%--------人眼检测部分开始---------------------%%%%%%%%%%%%%%%%%%%%%% videoObj = VideoReader('eye.mp4');%读视频文件 nframes = get(videoObj, 'NumberOfFrames');%获取视频文件帧个数 img = read(videoObj, 1);%读取第1帧，用于人脸检测 Eye_Detect = vision.CascadeObjectDetector('EyePairBig');%使用 Viola-Jones 算法，人脸检测工具箱中的人眼部分 Eyes=step(Eye_Detect,img);%从第一张照片中检测出人眼，函数返回的是人眼的位置 hold on; imshow(img);%显示第一张照片 for i = 1:size(Eyes,1) rectangle('Position',Eyes(i,:),'LineWidth',1,'LineStyle','-','EdgeColor','r');%将上面人眼的位置，用一个矩形框框起来，显示 end title('Eyes Detection');%标注眼睛检测 hold off; pause(0.000001)%暂停一小会，休息一下，马上回来 rect=Eyes(1,:);%保存rect检测到的位置 temp=img(rect(2):rect(2)+rect(4),rect(1):rect(1)+rect(3),:);%将检测到的眼睛部分的图片提取出来 [a,b,c]=size(temp); %返回图片的维数 %% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%计算目标图像的权值矩阵%%%%%%%%%%%%%%%%%%%%%%% y(1)=a/2; y(2)=b/2; tic_x=rect(1)+rect(3)/2; tic_y=rect(2)+rect(4)/2; m_wei=zeros(a,b);%权值矩阵 h=y(1)^2+y(2)^2 ;%带宽 for i=1:a for j=1:b dist=(i-y(1))^2+(j-y(2))^2; m_wei(i,j)=1-dist/h; %epanechnikov profile 核函数 end end C=1/sum(sum(m_wei));%归一化系数 %计算目标权值直方图qu %hist1=C*wei_hist(temp,m_wei,a,b);%target model hist1=zeros(1,4096); for i=1:a for j=1:b %rgb颜色空间量化为16*16*16 bins q_r=fix(double(temp(i,j,1))/16); %fix为趋近0取整函数，红色 q_g=fix(double(temp(i,j,2))/16); %绿色 q_b=fix(double(temp(i,j,3))/16); %蓝色 q_temp=q_r*256+q_g*16+q_b; %设置每个像素点红色、绿色、蓝色分量所占比重 hist1(q_temp+1)= hist1(q_temp+1)+m_wei(i,j); %计算直方图统计中每个像素点占的权重 end end hist1=hist1*C; rect(3)=ceil(rect(3)); rect(4)=ceil(rect(4)); %% %%%%%%%%%%%%%%%%%%%%%%%%%读取序列图像%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% for l=1:nframes Im= read(videoObj, l);%读取第i帧 num=0; Y=[2,2]; %%%%%%%mean shift迭代 while((Y(1)^2+Y(2)^2>0.5)&num<20) %迭代条件 num=num+1; temp1=imcrop(Im,rect); %计算侯选区域直方图 %hist2=C*wei_hist(temp1,m_wei,a,b);%target candidates pu hist2=zeros(1,4096); for i=1:a for j=1:b q_r=fix(double(temp1(i,j,1))/16); q_g=fix(double(temp1(i,j,2))/16); q_b=fix(double(temp1(i,j,3))/16); q_temp1(i,j)=q_r*256+q_g*16+q_b; hist2(q_temp1(i,j)+1)= hist2(q_temp1(i,j)+1)+m_wei(i,j); end end hist2=hist2*C; %figure(2); %subplot(1,2,1); %plot(hist2); % hold on; w=zeros(1,4096); for i=1:4096 if(hist2(i)~=0) %不等于 w(i)=sqrt(hist1(i)/hist2(i)); else w(i)=0; end end %变量初始化 sum_w=0; xw=[0,0]; for i=1:a; for j=1:b sum_w=sum_w+w(uint32(q_temp1(i,j))+1); xw=xw+w(uint32(q_temp1(i,j))+1)*[i-y(1)-0.5,j-y(2)-0.5]; end end Y=xw/sum_w; %中心点位置更新 rect(1)=rect(1)+Y(2); rect(2)=rect(2)+Y(1); end %%%跟踪轨迹矩阵%%% tic_x=[tic_x;rect(1)+rect(3)/2]; tic_y=[tic_y;rect(2)+rect(4)/2]; v1=rect(1); v2=rect(2); v3=rect(3); v4=rect(4); %% %%%显示跟踪结果%%% %subplot(1,2,2); imshow(uint8(Im)); title('目标跟踪结果及其运动轨迹'); hold on; plot([v1,v1+v3],[v2,v2],[v1,v1],[v2,v2+v4],[v1,v1+v3],[v2+v4,v2+v4],[v1+v3,v1+v3],[v2,v2+v4],'LineWidth',2,'Color','r'); plot(tic_x,tic_y,'LineWidth',2,'Color','b'); hold off; pause(0.000001) end
matlab官网效果图
