基于卡尔曼滤波的视频目标跟踪matlab源码

clear,clc % compute the background image Imzero = zeros(240,320,3); for i = 1:5 Im{i} = double(imread(['DATA/',int2str(i),'.jpg'])); Imzero = Im{i}+Imzero; end Imback = Imzero/5; [MR,MC,Dim] = size(Imback); % Kalman filter initialization R=[[0.2845,0.0045]',[0.0045,0.0455]']; H=[[1,0]',[0,1]',[0,0]',[0,0]']; Q=0.01*eye(4); P = 100*eye(4); dt=1; A=[[1,0,0,0]',[0,1,0,0]',[dt,0,1,0]',[0,dt,0,1]']; g = 6; % pixels^2/time step Bu = [0,0,0,g]'; kfinit=0; x=zeros(100,4); % loop over all images for i = 1 : 60 % load image Im = (imread(['DATA/',int2str(i), '.jpg'])); imshow(Im) imshow(Im) Imwork = double(Im); %extract ball [cc(i),cr(i),radius,flag] = extractball(Imwork,Imback,i); if flag==0 continue end hold on for c = -1*radius: radius/20 : 1*radius r = sqrt(radius^2-c^2); plot(cc(i)+c,cr(i)+r,'g.') plot(cc(i)+c,cr(i)-r,'g.') end % Kalman update i if kfinit==0 xp = [MC/2,MR/2,0,0]' else xp=A*x(i-1,:)' + Bu end kfinit=1; PP = A*P*A' + Q K = PP*H'*inv(H*PP*H'+R) x(i,:) = (xp + K*([cc(i),cr(i)]' - H*xp))'; x(i,:) [cc(i),cr(i)] P = (eye(4)-K*H)*PP hold on for c = -1*radius: radius/20 : 1*radius r = sqrt(radius^2-c^2); plot(x(i,1)+c,x(i,2)+r,'r.') plot(x(i,1)+c,x(i,2)-r,'r.') end pause(0.3) end % show positions figure plot(cc,'r*') hold on plot(cr,'g*') %end %estimate image noise (R) from stationary ball posn = [cc(55:60)',cr(55:60)']; mp = mean(posn); diffp = posn - ones(6,1)*mp; Rnew = (diffp'*diffp)/5;