基于MATLAB的MeanShift运动目标跟踪 matlab程序

约定不等于承诺〃 2022-09-11 09:29 261阅读 0赞

一、思路简介

1.截取跟踪目标矩阵rect

2.求取跟踪目标的加权直方图hist1

3.读取视频序列中的一帧， 先随机取一块与rect等大的矩形，计算加权直方图hist2。

4.计算两者比重函数，如果后者差距过大， 更新新的矩阵中心Y，进行迭代（MeanShift是一种变步长可以迅速接近概率密度峰值的方法），直至一定条件后停止。

二、源程序参考

function \[\] = select()  
close all;  
clear all;  
%%%%%%%%%%%%%%%%%%根据一幅目标全可见的图像圈定跟踪目标%%%%%%%%%%%%%%%%%%%%%%%  
I=imread('E:\\数字图像处理\\6\\2\\18.bmp');  
figure(1);  
imshow(I);  
  
  
\[temp,rect\]=imcrop(I);  
\[a,b,c\]=size(temp);  
  
  
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%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  
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,a\*b);  
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  
q\_g=fix(double(temp(i,j,2))/16);  
q\_b=fix(double(temp(i,j,3))/16);  
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  
myfile=dir('\*.bmp');  
lengthfile=length(myfile);  
  
  
for l=1:lengthfile  
Im=imread(myfile(l).name);  
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,a\*b);  
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,a\*b);  
for i=1:a\*b  
if(hist2(i)~=0)  
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');  
  
  
end

结果截图：

![v2-1633afbc5e85ecb8199ccb67fd5b4919\_b.jpg][v2-1633afbc5e85ecb8199ccb67fd5b4919_b.jpg]

![v2-6f2d0fbfa1d49d3014ca2e6f78944ef8\_b.jpg][v2-6f2d0fbfa1d49d3014ca2e6f78944ef8_b.jpg]

[v2-1633afbc5e85ecb8199ccb67fd5b4919_b.jpg]: /images/20220828/1704b07200e54411ba1884c6b9f3aa04.png
[v2-6f2d0fbfa1d49d3014ca2e6f78944ef8_b.jpg]: /images/20220828/0ba317ef5d574b3dabb6ec9bc826727f.png