matlab实现的人体识别与跟踪算法

clear,clc %读入背景 Imzero = zeros(240,360,3); Imzero=imread('background.jpg'); Imback=double(Imzero); [MR,MC,Dim] = size(Imback); %求出Vx 和 Vy I0 = imread(strcat('man',int2str(0)) ,'jpg'); Imwork = double(I0); [cc(1),cr(1),flag, stats,labeled,index] = extractman(Imwork,Imback,1); I79 = imread(strcat('man',int2str(79)) ,'jpg'); Imwork = double(I79); [cc(80),cr(80),flag, stats,labeled,index] = extractman(Imwork,Imback,80); Sx = cc(1)-cc(80); Sy = cr(1)-cr(80); Vx = Sx/80; Vy = Sy/80; % Kalman filter initialization dt=1; A=[[1,0,0,0]',[0,1,0,0]',[-Vx*dt,0,1,0]',[0,-Vy*dt,0,1]']; C=[[1,0]',[0,1]',[0,0]',[0,0]']; Q=0.5*eye(4); R=[[0.2845,0.0045]',[0.0045,0.0455]']; x=zeros(80,4); P = 80*eye(4); I = eye(4); firstinit=1; % loop over all images h = 1; for i = 1 : 20 % 装入各帧 Im = imread(strcat('man',int2str(i*4-1)) ,'jpg'); if h > 0 figure(h); clf; end imshow(Im) Imwork = double(Im); %目标检测 [cc(i),cr(i),flag, stats,labeled,index] = extractman(Imwork,Imback,i); %判断是否提取到目标特征 if flag==0 continue end %绘制检测结果的矩形框 rectangle('Position', round(stats(index).BoundingBox),'EdgeColor','g'); % 卡尔曼滤波 if firstinit == 1; xp = [280,145,0,0]'; fristinit = 0; else xp=A*x(i-1,:)'; end PP = A*P*A'+Q; K = PP*C'*inv(C*PP*C'+R); x(i,:) = (xp + K*([cc(i),cr(i)]' - C*xp))'; x(i,:) [cc(i),cr(i)] P = (eye(4)-K*C)*PP; %P = (I - K*C)*PP*(I - K*C)' + K*R*K'; %inv(P) = inv(PP) + C'*inv(R)*K; %绘制跟踪矩形框 [row, col, v] = find(labeled == index); width = abs(max(col)-min(col)); hight = abs(max(row)-min(row)); xdownleft = x(i,1)-width/2; ydownleft = x(i,2)-hight/2; hold on if width > 0 && hight > 0 rectangle('Position',[xdownleft,ydownleft,width, hight],'EdgeColor', 'r'); %plot(x(i,1),x(i,2),'r*'); end %各帧之间的延迟 pause(0.3) end %显示检测中心点的轨迹 figure plot(cc,'r*') hold on plot(cr,'g*') end %显示跟踪中心点的轨迹 figure plot(x(:,1),'rx') hold on plot(x(:,2),'gx') end