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2.部分仿真图预览
3.算法概述
光流法(Optical flow or optic flow)是关于视域中的物体运动检测中的概念。用来描述相对于观察者的运动所造成的观测目标、表面或边缘的运动。光流法在样型识别、计算机视觉以及其他影像处理领域中非常有用，可用于运动检测、物件切割、碰撞时间与物体膨胀的计算、运动补偿编码，或者通过物体表面与边缘进行立体的测量等等。
4.部分源码
fr_f1=rgb2gray(f1);
fr_f40=rgb2gray(f40);
Xn=double(fr_f1);
Xnp1=double(fr_f40);
%get image size and adjust for border 获取图像对边界进行调整
[h,w]=size(fr_f1);
hm5=h-5; wm5=w-5;
z=zeros(h,w); v1=z; v2=z;
%initialize 初始化
dsx2=v1; dsx1=v1; dst=v1;
alpha2=625;
imax=20;
%Calculate gradients 计算梯度
dst(5:hm5,5:wm5) = ( Xnp1(6:hm5+1,6:wm5+1)-Xn(6:hm5+1,6:wm5+1) + Xnp1(6:hm5+1,5:wm5)-Xn(6:hm5+1,5:wm5)+ Xnp1(5:hm5,6:wm5+1)-Xn(5:hm5,6:wm5+1) +Xnp1(5:hm5,5:wm5)-Xn(5:hm5,5:wm5))/4;
dsx2(5:hm5,5:wm5) = ( Xnp1(6:hm5+1,6:wm5+1)-Xnp1(5:hm5,6:wm5+1) + Xnp1(6:hm5+1,5:wm5)-Xnp1(5:hm5,5:wm5)+ Xn(6:hm5+1,6:wm5+1)-Xn(5:hm5,6:wm5+1) +Xn(6:hm5+1,5:wm5)-Xn(5:hm5,5:wm5))/4;
dsx1(5:hm5,5:wm5) = ( Xnp1(6:hm5+1,6:wm5+1)-Xnp1(6:hm5+1,5:wm5) + Xnp1(5:hm5,6:wm5+1)-Xnp1(5:hm5,5:wm5)+ Xn(6:hm5+1,6:wm5+1)-Xn(6:hm5+1,5:wm5) +Xn(5:hm5,6:wm5+1)-Xn(5:hm5,5:wm5))/4;
for i=1:imax
delta=(dsx1.*v1+dsx2.*v2+dst)./(alpha2+dsx1.^2+dsx2.^2);
v1=v1-dsx1.*delta;
v2=v2-dsx2.*delta;
end;
A181
