基于MATLAB的人脸朝向识别

《基于MATLAB的人脸朝向识别》由会员上传分享，免费在线阅读，更多相关内容在教育资源-天天文库。

1、clearallclc;%%人脸特征向量提取%人数M=10;%人脸朝向类别数N=5;%特征向量提取pixel_value=feature_extraction(M,N);%%训练集/测试集产生%产生图像序号的随机序列rand_label=randperm(M*N);%人脸朝向标号direction_label=repmat(1:N,1,M);%训练集train_label=rand_label(1:30);P_train=pixel_value(train_label,:)';Tc_train=direction_label(train_label);T_train=ind2vec(Tc_tr

2、ain);%测试集test_label=rand_label(31:end);P_test=pixel_value(test_label,:)';Tc_test=direction_label(test_label);%%K-fold交叉验证确定最佳神经元个数k_fold=10;Indices=crossvalind('Kfold',size(P_train,2),k_fold);error_min=10e10;best_number=1;best_input=[];best_output=[];best_train_set_index=[];best_validation_set_index

3、=[];h=waitbar(0,'正在寻找最佳神经元个数.....');fori=1:k_fold%验证集标号validation_set_index=(Indices==i);%训练集标号train_set_index=~validation_set_index;%验证集validation_set_input=P_train(:,validation_set_index);validation_set_output=T_train(:,validation_set_index);%训练集train_set_input=P_train(:,train_set_index);train_set

4、_output=T_train(:,train_set_index);fornumber=10:30forj=1:5rate{j}=length(find(Tc_train(:,train_set_index)==j))/length(find(train_set_index==1));endnet=newlvq(minmax(train_set_input),number,cell2mat(rate));%设置网络参数net.trainParam.epochs=100;net.trainParam.show=10;net.trainParam.lr=0.1;net.trainParam.go

5、al=0.001;%训练网络net=train(net,train_set_input,train_set_output);waitbar(((i-1)*21+number)/219,h);%%仿真测试T_sim=sim(net,validation_set_input);Tc_sim=vec2ind(T_sim);error=length(find(Tc_sim~=Tc_train(:,validation_set_index)));iferror

6、est_output=train_set_output;best_train_set_index=train_set_index;best_validation_set_index=validation_set_index;endendenddisp(['经过交叉验证，得到的最佳神经元个数为：'num2str(best_number)]);close(h);%%创建LVQ网络fori=1:5rate{i}=length(find(Tc_train(:,best_train_set_index)==i))/length(find(best_train_set_index==1));endnet=

7、newlvq(minmax(best_input),best_number,cell2mat(rate),0.01);%设置训练参数net.trainParam.epochs=100;net.trainParam.goal=0.001;net.trainParam.lr=0.1;%%训练网络net=train(net,best_input,best_output);%%人脸识别测试T_sim=si