list=dir('MSR-Action3D\a01\*.jpg');
G=[];
n=0;
for k=1:3:length(list)
% Load image
img1=imread(strcat('MSR-Action3D\a01\',list(k).name));
img2=imread(strcat('MSR-Action3D\a01\',list(k+1).name));
img3=imread(strcat('MSR-Action3D\a01\',list(k+2).name));
n=n+1;
% Parameters:
clear param
param.imageSize = [256 256]; % it works also with non-square images
param.orientationsPerScale = [8 8 8 8];
param.numberBlocks = 4;
param.fc_prefilt = 4;
% Computing gist requires 1) prefilter image, 2) filter image and collect
% output energies
[gist1, param] = LMgist(img1, '', param);
[gist2, param] = LMgist(img2, '', param);
[gist3, param] = LMgist(img3, '', param);
gist=[gist1 gist2 gist3];
G(:,n)=gist';
end
----------------------------------------------------2018.4.15--------------------------------------------------------------------
Glist=[];%特征列表
Tlist=[];%标签列表
maindir ='MSR-Action3D';
subdir = dir(maindir); %先确定子文件夹
for i = 1:length(subdir)
if(isequal(subdir(i).name, '.') || ...
isequal(subdir(i).name, '..') || ...
~subdir(i).isdir) % 如果不是目录跳过
continue;
end
subdirpath = fullfile(maindir, subdir( i ).name, '*.jpg');
list = dir(subdirpath); % 在这个子文件夹下找后缀为jpg的文件
G=[];
T=[];
n=0;
for k=1:3:length(list)
% Load image
img1=imread(fullfile( maindir, subdir(i).name,list(k).name));
img2=imread(fullfile( maindir, subdir(i).name,list(k+1).name));
img3=imread(fullfile( maindir, subdir(i).name,list(k+2).name));
n=n+1;
% Parameters:
clear param
param.imageSize = [256 256]; % it works also with non-square images
param.orientationsPerScale = [8 8 8 8];
param.numberBlocks = 4;
param.fc_prefilt = 4;
% Computing gist requires 1) prefilter image, 2) filter image and collect
% output energies
[gist1, param] = LMgist(img1, '', param);
[gist2, param] = LMgist(img2, '', param);
[gist3, param] = LMgist(img3, '', param);
gist=[gist1 gist2 gist3];
G(n,:)=gist;
T(n,:)=i-2;
end
Glist=[Glist;G];
Tlist=[Tlist;T];
end
% load('Glist.mat');
% load('Tlist.mat');
% Sparse_Train_Features = sparse(Glist);
% Sparse_Test_Features = sparse(Test_Images_Features);
% Sparse_Train_Label = sparse(Tlist);
% Sparse_Test_Label = sparse(GT_Test_Images);
%
% libsvmwrite('train.txt', Sparse_Train_Label, Sparse_Train_Features);
% libsvmwrite('test.txt', Sparse_Test_Label, Sparse_Test_Features);
---------------------------------------------------------2018.4.19---------------------------------------------------------------
Glist=[];%特征列表
Tlist=[];%标签列表
maindir = 'MSR-Action3D\';
% AS1=['a02', 'a03', 'a05', 'a06', 'a10', 'a13', 'a18', 'a20'];
% T1=[02,03,05,06,10,13,18,20];
% AS1=['a01', 'a04', 'a07', 'a08', 'a09', 'a11', 'a14', 'a12'];
% T1=[01,04,07,08,09,11,14,12];
AS1=[ 'a06', 'a14', 'a15', 'a16', 'a17', 'a18', 'a19', 'a20'];
T1=[06,14,15,16,17,18,19,20];
NumAct = 8; % number of actions in each subset
for i=1:NumAct
action=AS1((i-1)*3+1:i*3);
subdir=strcat(maindir,action,'\');
subdirpath = fullfile(subdir, '*.jpg');
list = dir(subdirpath);
G=[];
T=[];
n=0;
for k=1:3:length(list)
% Load image
img1=imread(fullfile(subdir,list(k).name));
img2=imread(fullfile(subdir,list(k+1).name));
img3=imread(fullfile(subdir,list(k+2).name));
n=n+1;
% Parameters:
clear param
param.imageSize = [256 256]; % it works also with non-square images
param.orientationsPerScale = [8 8 8 8];
param.numberBlocks = 4;
param.fc_prefilt = 4;
% Computing gist requires 1) prefilter image, 2) filter image and collect
% output energies
[gist1, param] = LMgist(img1, '', param);
[gist2, param] = LMgist(img2, '', param);
[gist3, param] = LMgist(img3, '', param);
gist=[gist1 gist2 gist3];
G(n,:)=gist;
T(n,:)=T1(i);
end
Glist=[Glist;G];
Tlist=[Tlist;T];
end