Adapting training scripts to new output format (Bosphorus and BP4D).

matlab_version/AU_training/data extraction/extract_features_FERA_2011.m

@@ -9,10 +9,11 @@ end
 find_FERA2011;
 
 output_dir = 'E:\datasets\face_datasets_processed\fera2011';
+FERA2011_dir = [FERA2011_dir, '/../'];
 
 % Go two levels deep
-fera_dirs = dir([FERA2011_dir, '/train*']);
+fera_dirs = dir([FERA2011_dir, '*']);
-
+fera_dirs = fera_dirs(3:end);
 parfor f1=1:numel(fera_dirs)
 
     fera_dirs_level_2 = dir([FERA2011_dir, fera_dirs(f1).name]);

matlab_version/AU_training/data extraction/extract_features_SEMAINE.m

@@ -10,7 +10,7 @@ find_SEMAINE;
 
 % Go two levels deep
 semaine_dirs = train_recs;
-output_dir = 'E:\datasets\face_datasets_processed\semaine';
+output_dir = 'E:\datasets\face_datasets_processed\semaine\train';
 
 parfor f1=1:numel(semaine_dirs)
 
@@ -33,7 +33,7 @@ end
 
 %%
 semaine_dirs = devel_recs;
-out_loc = [SEMAINE_dir, '../processed_data/devel/'];
+output_dir = 'E:\datasets\face_datasets_processed\semaine\devel';
 
 parfor f1=1:numel(semaine_dirs)
 

matlab_version/AU_training/data extraction/find_Bosphorus.m

@@ -6,7 +6,7 @@ else
     fprintf('Bosphorus dataset location not found (or not defined)\n'); 
 end
 
-hog_data_dir = ['D:\Datasets\face_datasets'];
+hog_data_dir = ['E:\Datasets\face_datasets_processed\bosph'];
 
 all_recs = dir([Bosphorus_dir, '/BosphorusDB/BosphorusDB/bs*']);
 all_recs_mat = cat(1, all_recs.name);

matlab_version/AU_training/experiments/BP4D/Prepare_HOG_AU_data_generic.m

@@ -1,5 +1,5 @@
 function [data_train, labels_train, data_devel, labels_devel, raw_devel, PC, means_norm, stds_norm, valid_ids_test] = ...
-    Prepare_HOG_AU_data_generic(train_users, devel_users, au_train, bp4d_dir, hog_data_dir, pca_file)
+    Prepare_HOG_AU_data_generic(train_users, devel_users, au_train, bp4d_dir, features_dir)
 
 %%
 addpath(genpath('../../data extraction/'));
@@ -11,9 +11,9 @@ labels_other = cat(1, labels_other{:});
 % First extracting the labels
 [ labels_train, valid_ids_train, vid_ids_train ] = extract_BP4D_labels(bp4d_dir, train_users, au_train);
 
-train_geom_data = Read_geom_files(train_users, hog_data_dir);
+train_geom_data = Read_geom_files(train_users, features_dir);
 % Reading in the HOG data (of only relevant frames)
-[train_appearance_data, valid_ids_train_hog, vid_ids_train_string] = Read_HOG_files(train_users, hog_data_dir);
+[train_appearance_data, valid_ids_train_hog, vid_ids_train_string] = Read_HOG_files(train_users, features_dir);
 train_appearance_data = cat(2, train_appearance_data, train_geom_data);
 
 % Subsample the data to make training quicker
@@ -67,8 +67,8 @@ vid_ids_train_string = vid_ids_train_string(reduced_inds,:);
 [ labels_devel, valid_ids_devel, vid_ids_devel ] = extract_BP4D_labels(bp4d_dir, devel_users, au_train);
 
 % Reading in the HOG data (of only relevant frames)
-devel_geom_data = Read_geom_files(devel_users, hog_data_dir);
+devel_geom_data = Read_geom_files(devel_users, features_dir);
-[devel_appearance_data, valid_ids_devel_hog, vid_ids_devel_string] = Read_HOG_files(devel_users, hog_data_dir);
+[devel_appearance_data, valid_ids_devel_hog, vid_ids_devel_string] = Read_HOG_files(devel_users, features_dir);
 devel_appearance_data = cat(2, devel_appearance_data, devel_geom_data);
 
 labels_devel = cat(1, labels_devel{:});

matlab_version/AU_training/experiments/BP4D/Prepare_HOG_AU_data_generic_intensity.m

@@ -1,5 +1,5 @@
 function [data_train, labels_train, vid_ids_train_string, data_devel, labels_devel, vid_ids_devel_string, raw_devel, PC, means_norm, stds_norm, success_devel] = ...
-    Prepare_HOG_AU_data_generic_intensity(train_users, devel_users, au_train, bp4d_dir, hog_data_dir)
+    Prepare_HOG_AU_data_generic_intensity(train_users, devel_users, au_train, bp4d_dir, features_dir)
 
 %%
 addpath(genpath('../data extraction/'));
@@ -10,10 +10,10 @@ au_other = setdiff([6, 10, 12, 14, 17], au_train);
 [ labels_other, ~, ~ ] = extract_BP4D_labels_intensity(bp4d_dir, train_users, au_other);
 labels_other = cat(1, labels_other{:});
 
-train_geom_data = Read_geom_files(train_users, hog_data_dir);
+train_geom_data = Read_geom_files(train_users, features_dir);
 
 % Reading in the HOG data (of only relevant frames)
-[train_appearance_data, valid_ids_train_hog, vid_ids_train_string] = Read_HOG_files(train_users, hog_data_dir);
+[train_appearance_data, valid_ids_train_hog, vid_ids_train_string] = Read_HOG_files(train_users, features_dir);
 train_appearance_data = cat(2, train_appearance_data, train_geom_data);
 
 % Subsample the data to make training quicker
@@ -65,9 +65,9 @@ end
 % First extracting the labels
 [ labels_devel, valid_ids_devel, vid_ids_devel ] = extract_BP4D_labels_intensity(bp4d_dir, devel_users, au_train);
 
-devel_geom_data = Read_geom_files(devel_users, hog_data_dir);
+devel_geom_data = Read_geom_files(devel_users, features_dir);
 % Reading in the HOG data (of only relevant frames)
-[devel_appearance_data, valid_ids_devel_hog, vid_ids_devel_string] = Read_HOG_files(devel_users, hog_data_dir);
+[devel_appearance_data, valid_ids_devel_hog, vid_ids_devel_string] = Read_HOG_files(devel_users, features_dir);
 devel_appearance_data = cat(2, devel_appearance_data, devel_geom_data);
 
 valid_ids_devel = logical(cat(1, valid_ids_devel{:}));

matlab_version/AU_training/experiments/BP4D/Prepare_HOG_AU_data_generic_intensity_dynamic.m

@@ -1,5 +1,5 @@
 function [data_train, labels_train, vid_ids_train_string, data_devel, labels_devel, vid_ids_devel_string, raw_devel, PC, means_norm, stds_norm, success_devel] = ...
-    Prepare_HOG_AU_data_generic_intensity_dynamic(train_users, devel_users, au_train, bp4d_dir, hog_data_dir)
+    Prepare_HOG_AU_data_generic_intensity_dynamic(train_users, devel_users, au_train, bp4d_dir, features_dir)
 
 %%
 addpath(genpath('../data extraction/'));
@@ -10,10 +10,10 @@ au_other = setdiff([6, 10, 12, 14, 17], au_train);
 [ labels_other, ~, ~ ] = extract_BP4D_labels_intensity(bp4d_dir, train_users, au_other);
 labels_other = cat(1, labels_other{:});
 
-train_geom_data = Read_geom_files_dynamic(train_users, hog_data_dir);
+train_geom_data = Read_geom_files_dynamic(train_users, features_dir);
 
 % Reading in the HOG data (of only relevant frames)
-[train_appearance_data, valid_ids_train_hog, vid_ids_train_string] = Read_HOG_files_dynamic_pp(train_users, hog_data_dir);
+[train_appearance_data, valid_ids_train_hog, vid_ids_train_string] = Read_HOG_files_dynamic_pp(train_users, features_dir);
 train_appearance_data = cat(2, train_appearance_data, train_geom_data);
 
 % Subsample the data to make training quicker
@@ -65,9 +65,9 @@ end
 % First extracting the labels
 [ labels_devel, valid_ids_devel, vid_ids_devel ] = extract_BP4D_labels_intensity(bp4d_dir, devel_users, au_train);
 
-devel_geom_data = Read_geom_files_dynamic(devel_users, hog_data_dir);
+devel_geom_data = Read_geom_files_dynamic(devel_users, features_dir);
 % Reading in the HOG data (of only relevant frames)
-[devel_appearance_data, valid_ids_devel_hog, vid_ids_devel_string] = Read_HOG_files_dynamic_pp(devel_users, hog_data_dir);
+[devel_appearance_data, valid_ids_devel_hog, vid_ids_devel_string] = Read_HOG_files_dynamic_pp(devel_users, features_dir);
 devel_appearance_data = cat(2, devel_appearance_data, devel_geom_data);
 
 valid_ids_devel = logical(cat(1, valid_ids_devel{:}));

matlab_version/AU_training/experiments/BP4D/Read_geom_files.m

@@ -7,10 +7,10 @@ function [geom_data, valid_ids] = Read_geom_files(users, hog_data_dir)
     
     for i=1:numel(users)
         
-        geom_files = dir([hog_data_dir, '/train/', users{i} '*.params.txt']);
+        geom_files = dir([hog_data_dir, '/train/', users{i} '*.csv']);
         geom_dir = [hog_data_dir, '/train/'];
         if(isempty(geom_files))
-            geom_files = dir([hog_data_dir, '/devel/', users{i} '*.params.txt']);
+            geom_files = dir([hog_data_dir, '/devel/', users{i} '*.csv']);
             geom_dir = [hog_data_dir, '/devel/'];
         end
         
@@ -20,15 +20,26 @@ function [geom_data, valid_ids] = Read_geom_files(users, hog_data_dir)
             m_file = [geom_dir, '/' nm '.params.mat'];
               
             if(~exist(m_file, 'file'))
+                if(i == 1)
+                    tab = readtable(geom_file);
+                    column_names = tab.Properties.VariableNames; 
+                    valid_ind = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'valid'));
+                    shape_inds = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'p_'));
+                end
+        
                 res = dlmread(geom_file, ',', 1, 0);
-                save(m_file, 'res');
+                
+                valid = res(:, valid_ind) > 0.7;        
+                res = res(:, shape_inds);
+                
+                % Do not consider global parameters
+                res = res(:, 7:end);
+                
+                save(m_file, 'res', 'valid');
             else
                 load(m_file);
             end
                     
-            valid = res(:, 4);
-            res = res(:, 11:end);
-                    
             actual_locs = res * V';
             res = cat(2, actual_locs, res);
             

matlab_version/AU_training/experiments/BP4D/Read_geom_files_dynamic.m

@@ -7,10 +7,10 @@ function [geom_data, valid_ids] = Read_geom_files_dynamic(users, hog_data_dir)
     
     for i=1:numel(users)
         
-        geom_files = dir([hog_data_dir, '/train/', users{i} '*.params.txt']);
+        geom_files = dir([hog_data_dir, '/train/', users{i} '*.csv']);
         geom_dir = [hog_data_dir, '/train/'];
         if(isempty(geom_files))
-            geom_files = dir([hog_data_dir, '/devel/', users{i} '*.params.txt']);
+            geom_files = dir([hog_data_dir, '/devel/', users{i} '*.csv']);
             geom_dir = [hog_data_dir, '/devel/'];
         end
         
@@ -22,15 +22,26 @@ function [geom_data, valid_ids] = Read_geom_files_dynamic(users, hog_data_dir)
             m_file = [geom_dir, '/' nm '.params.mat'];
               
             if(~exist(m_file, 'file'))
+                if(i == 1)
+                    tab = readtable(geom_file);
+                    column_names = tab.Properties.VariableNames; 
+                    valid_ind = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'valid'));
+                    shape_inds = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'p_'));
+                end
+        
                 res = dlmread(geom_file, ',', 1, 0);
-                save(m_file, 'res');
+                
+                valid = res(:, valid_ind) > 0.7;        
+                res = res(:, shape_inds);
+                
+                % Do not consider global parameters
+                res = res(:, 7:end);
+                
+                save(m_file, 'res', 'valid');
             else
                 load(m_file);
             end
 
-            valid = res(:, 4);
-            res = res(:, 11:end);
-                    
             actual_locs = res * V';
             res = cat(2, actual_locs, res);
             

matlab_version/AU_training/experiments/BP4D/Script_HOG_SVM_dynamic.m

@@ -32,7 +32,7 @@ for a=1:numel(aus)
     rest_aus = setdiff(all_aus, au);        
 
     % load the training and testing data for the current fold
-    [train_samples, train_labels, valid_samples, valid_labels, ~, PC, means, scaling] = Prepare_HOG_AU_data_generic_dynamic(train_recs, devel_recs, au, BP4D_dir, hog_data_dir_BP4D, pca_loc);
+    [train_samples, train_labels, valid_samples, valid_labels, ~, PC, means, scaling] = Prepare_HOG_AU_data_generic_dynamic(train_recs, devel_recs, au, BP4D_dir, hog_data_dir_BP4D);
 
     train_samples = sparse(train_samples);
     valid_samples = sparse(valid_samples);

matlab_version/AU_training/experiments/BP4D/Script_HOG_SVM_static.m

@@ -32,7 +32,7 @@ for a=1:numel(aus)
     rest_aus = setdiff(all_aus, au);        
 
     % load the training and testing data for the current fold
-    [train_samples, train_labels, valid_samples, valid_labels, ~, PC, means, scaling] = Prepare_HOG_AU_data_generic(train_recs, devel_recs, au, BP4D_dir, hog_data_dir_BP4D, pca_loc);
+    [train_samples, train_labels, valid_samples, valid_labels, ~, PC, means, scaling] = Prepare_HOG_AU_data_generic(train_recs, devel_recs, au, BP4D_dir, hog_data_dir_BP4D);
 
     train_samples = sparse(train_samples);
     valid_samples = sparse(valid_samples);

matlab_version/AU_training/experiments/BP4D/Script_HOG_SVR_dynamic_shift.m

@@ -35,7 +35,7 @@ for a=1:numel(aus)
     rest_aus = setdiff(all_aus, au);        
     
     % load the training and testing data for the current fold
-    [train_samples, train_labels, ~, valid_samples, valid_labels, vid_ids_devel, ~, PC, means, scaling, success_devel] = Prepare_HOG_AU_data_generic_intensity(train_recs, devel_recs, au, BP4D_dir_int, hog_data_dir_BP4D, pca_loc);
+    [train_samples, train_labels, ~, valid_samples, valid_labels, vid_ids_devel, ~, PC, means, scaling, success_devel] = Prepare_HOG_AU_data_generic_intensity(train_recs, devel_recs, au, BP4D_dir_int, hog_data_dir_BP4D);
     
     ignore = valid_labels == 9;
     

matlab_version/AU_training/experiments/BP4D/Script_HOG_SVR_static_shift.m

@@ -35,7 +35,7 @@ for a=1:numel(aus)
     rest_aus = setdiff(all_aus, au);        
     
     % load the training and testing data for the current fold
-    [train_samples, train_labels, ~, valid_samples, valid_labels, vid_ids_devel, ~, PC, means, scaling, success_devel] = Prepare_HOG_AU_data_generic_intensity(train_recs, devel_recs, au, BP4D_dir_int, hog_data_dir_BP4D, pca_loc);
+    [train_samples, train_labels, ~, valid_samples, valid_labels, vid_ids_devel, ~, PC, means, scaling, success_devel] = Prepare_HOG_AU_data_generic_intensity(train_recs, devel_recs, au, BP4D_dir_int, hog_data_dir_BP4D);
     
     ignore = valid_labels == 9;
     

matlab_version/AU_training/experiments/BP4D/shared_defs.m

@@ -28,7 +28,7 @@ else
 end
 
 if(exist('BP4D_dir', 'var'))
-    hog_data_dir = [BP4D_dir, '../processed_data/'];
+    hog_data_dir = 'E:\datasets\face_datasets_processed\bp4d/';
 end
 
 train_recs = {'F001', 'F003', 'F005', 'F007', 'F009', 'F011', 'F013', 'F015', 'F017', 'F019', 'F021', 'F023', 'M001', 'M003', 'M005', 'M007', 'M009', 'M011', 'M013', 'M015' 'M017'};

matlab_version/AU_training/experiments/Bosphorus/Prepare_HOG_AU_data.m

@@ -1,5 +1,5 @@
 function [data_train, labels_train, data_devel, labels_devel, raw_devel, PC, means_norm, stds_norm, devel_ids, devel_success] = ...
-    Prepare_HOG_AU_data(train_users, devel_users, au_train, rest_aus, Bosphorus_dir, hog_data_dir)
+    Prepare_HOG_AU_data(train_users, devel_users, au_train, rest_aus, Bosphorus_dir, params_data_dir)
 
 %%
 addpath(genpath('../data extraction/'));
@@ -10,9 +10,8 @@ addpath(genpath('../data extraction/'));
 [ labels_other, ~, ~ ] = extract_Bosphorus_labels(Bosphorus_dir, train_users, rest_aus);
 
 % Reading in the HOG data (of only relevant frames)
-[train_appearance_data, valid_ids_train_hog, vid_ids_train_string] = Read_HOG_files(filenames, [hog_data_dir, '/hog_aligned_rigid_b']);
+[train_appearance_data, valid_ids_train_hog, vid_ids_train_string] = Read_HOG_files(filenames, params_data_dir);
 
-params_data_dir = [hog_data_dir, '/model_params_b'];
 [train_geom_data] = Read_geom_files(filenames,  params_data_dir);
 
 % Subsample the data to rebalance it
@@ -60,7 +59,7 @@ end
 [ labels_devel, valid_ids_devel, filenames_devel ] = extract_Bosphorus_labels(Bosphorus_dir, devel_users, au_train);
 
 % Reading in the HOG data (of only relevant frames)
-[devel_appearance_data, valid_ids_devel_hog, vid_ids_devel_string] = Read_HOG_files(filenames_devel, [hog_data_dir, '/hog_aligned_rigid_b']);
+[devel_appearance_data, valid_ids_devel_hog, vid_ids_devel_string] = Read_HOG_files(filenames_devel, params_data_dir);
 devel_success = valid_ids_devel_hog;
 devel_ids = vid_ids_devel_string;
 

matlab_version/AU_training/experiments/Bosphorus/Prepare_HOG_AU_data_dynamic.m

@@ -1,5 +1,5 @@
 function [data_train, labels_train, data_devel, labels_devel, raw_devel, PC, means_norm, stds_norm, devel_ids, devel_success] = ...
-    Prepare_HOG_AU_data_dynamic(train_users, devel_users, au_train, rest_aus, Bosphorus_dir, hog_data_dir)
+    Prepare_HOG_AU_data_dynamic(train_users, devel_users, au_train, rest_aus, Bosphorus_dir, params_data_dir)
 
 %%
 addpath(genpath('../data extraction/'));
@@ -10,9 +10,8 @@ addpath(genpath('../data extraction/'));
 [ labels_other, ~, ~ ] = extract_Bosphorus_labels(Bosphorus_dir, train_users, rest_aus);
 
 % Reading in the HOG data (of only relevant frames)
-[train_appearance_data, valid_ids_train_hog, vid_ids_train_string] = Read_HOG_files_dynamic(filenames, [hog_data_dir, '/hog_aligned_rigid_b']);
+[train_appearance_data, valid_ids_train_hog, vid_ids_train_string] = Read_HOG_files_dynamic(filenames, params_data_dir);
 
-params_data_dir = [hog_data_dir, '/model_params_b'];
 [train_geom_data] = Read_geom_files_dynamic(filenames,  params_data_dir);
 
 if(numel(train_users) > 0)
@@ -59,7 +58,7 @@ end
 [ labels_devel, valid_ids_devel, devel_files ] = extract_Bosphorus_labels(Bosphorus_dir, devel_users, au_train);
 
 % Reading in the HOG data (of only relevant frames)
-[devel_appearance_data, valid_ids_devel_hog, vid_ids_devel_string] = Read_HOG_files_dynamic(devel_files, [hog_data_dir, '/hog_aligned_rigid_b']);
+[devel_appearance_data, valid_ids_devel_hog, vid_ids_devel_string] = Read_HOG_files_dynamic(devel_files, params_data_dir);
 devel_success = valid_ids_devel_hog;
 devel_ids = vid_ids_devel_string;
 

matlab_version/AU_training/experiments/Bosphorus/Read_geom_files.m

@@ -7,12 +7,23 @@ function [geom_data, valid_ids] = Read_geom_files(users, model_param_data_dir)
     
     for i=1:numel(users)
     
-        geom_file = [model_param_data_dir, '/' users{i} '.txt'];
+        geom_file = [model_param_data_dir, '/' users{i} '.csv'];
+
+        if(i == 1)
+            tab = readtable(geom_file);
+            column_names = tab.Properties.VariableNames; 
+            valid_ind = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'confidence'));
+            shape_inds = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'p_'));
+        end
                 
         res = dlmread(geom_file, ',', 1, 0);    
 
-        valid = res(:, 4);        
+        % Check the confidence of detection
-        res = res(:, 11:end);
+        valid = res(:, valid_ind) > 0.7;        
+        res = res(:, shape_inds);
+        
+        % Do not consider global parameters
+        res = res(:, 7:end);
         
         actual_locs = res * V';
         res = cat(2, actual_locs, res);

matlab_version/AU_training/experiments/Bosphorus/Read_geom_files_dynamic.m

@@ -9,16 +9,24 @@ function [geom_data, valid_ids] = Read_geom_files_dynamic(users, model_param_dat
     
     for i=1:numel(users)
         
-        geom_file = [model_param_data_dir, '/' users{i} '.txt'];
+        geom_file = [model_param_data_dir, '/' users{i} '.csv'];
 
         user_files = cat(1, user_files, str2num(users{i}(3:5)));
 
-        m_file = [model_param_data_dir, '/', users{i}, '.mat'];
+        if(i == 1)
+            tab = readtable(geom_file);
+            column_names = tab.Properties.VariableNames; 
+            valid_ind = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'confidence'));
+            shape_inds = cellfun(@(x) ~isempty(x) && x==1, strfind(column_names, 'p_'));
+        end
                 
         res = dlmread(geom_file, ',', 1, 0);    
 
-        valid = res(:, 4);        
+        valid = res(:, valid_ind) > 0.7;     
-        res = res(:, 11:end);
+        res = res(:, shape_inds);
+        
+        % Do not consider global parameters
+        res = res(:, 7:end);
         
         actual_locs = res * V';
         res = cat(2, actual_locs, res);

matlab_version/AU_training/experiments/Bosphorus/Script_HOG_SVR_train_dyn.m

@@ -51,9 +51,9 @@ for a=1:numel(aus)
 
     svs = bsxfun(@times, PC, 1./scaling') * w;
 
-    name = sprintf('models/AU_%d_dyn_intensity.dat', au);
+    name = sprintf('models/AU_%d_static_intensity.dat', au);
 
-    write_lin_dyn_svr(name, means, svs, b);
+    write_lin_dyn_svr(name, means, svs, b, 0);
 
     name = sprintf('results_Bosphorus_devel/AU_%d_dyn_intensity.mat', au);
 

matlab_version/AU_training/pca_generation/createGenericFaceModel.m

@@ -1,48 +1,93 @@
 clear;
+face_processed_dir = 'E:\datasets\face_datasets_processed';
 
-%% CK+, FERA2011 and UNBC datasets
+%% CK+
-hog_dir = 'D:\Datasets/face_datasets/hog_aligned_rigid/';
+hog_dir = [face_processed_dir, '/ck+/'];
-hog_files = dir([hog_dir, '*.hog']);
+hog_files = dir([hog_dir '*.hog']);
-
 [appearance_data, valid_inds, vid_ids_train] = Read_HOG_files_small(hog_files, hog_dir);
 appearance_data = appearance_data(valid_inds,:);
 vid_ids_train = vid_ids_train(valid_inds,:);
 
+%% Bosphorus
+hog_dir = [face_processed_dir, '/bosph/'];
+hog_files = dir([hog_dir '*.hog']);
+
+% Remove non-frontal
+frontal = true(size(hog_files));
+for i = 1:numel(frontal)
+    if(~isempty(strfind(hog_files(i).name, 'YR')) || ~isempty(strfind(hog_files(i).name, 'PR'))|| ~isempty(strfind(hog_files(i).name, 'CR')))
+        frontal(i) = false;
+    end   
+end
+
+hog_files = hog_files(frontal);
+
+[appearance_data_tmp, valid_inds_tmp, vid_ids_train_tmp] = Read_HOG_files_small(hog_files, hog_dir);
+
+appearance_data_tmp = appearance_data_tmp(valid_inds_tmp,:);
+vid_ids_train_tmp = vid_ids_train_tmp(valid_inds_tmp,:);
+
+appearance_data = cat(1,appearance_data, appearance_data_tmp);
+vid_ids_train = cat(1,vid_ids_train, vid_ids_train_tmp);
+
+%% FERA2011
+hog_dir = [face_processed_dir, '/fera2011/'];
+hog_files = dir([hog_dir '*.hog']);
+[appearance_data_tmp, valid_inds_tmp, vid_ids_train_tmp] = Read_HOG_files_small(hog_files, hog_dir);
+
+ appearance_data_tmp = appearance_data_tmp(valid_inds_tmp,:);
+vid_ids_train_tmp = vid_ids_train_tmp(valid_inds_tmp,:);
+
+appearance_data = cat(1,appearance_data, appearance_data_tmp);
+vid_ids_train = cat(1,vid_ids_train, vid_ids_train_tmp);
+
+%% UNBC
+hog_dir = [face_processed_dir, '/unbc/'];
+hog_files = dir([hog_dir '*.hog']);
+[appearance_data_tmp, valid_inds_tmp, vid_ids_train_tmp] = Read_HOG_files_small(hog_files, hog_dir);
+
+appearance_data_tmp = appearance_data_tmp(valid_inds_tmp,:);
+vid_ids_train_tmp = vid_ids_train_tmp(valid_inds_tmp,:);
+
+appearance_data = cat(1,appearance_data, appearance_data_tmp);
+vid_ids_train = cat(1,vid_ids_train, vid_ids_train_tmp);
+
+
+
 %% DISFA
-hog_dir = 'D:\Datasets\DISFA\hog_aligned_rigid/';
+hog_dir = [face_processed_dir, '/disfa/'];
-hog_files = dir([hog_dir, '*.hog']);
+hog_files = dir([hog_dir '*.hog']);
 
-[appearance_data_disfa, valid_inds, vid_ids_train_disfa] = Read_HOG_files_small(hog_files, hog_dir, 100);
+[appearance_data_tmp, valid_inds_tmp, vid_ids_train_tmp] = Read_HOG_files_small(hog_files, hog_dir);
 
-appearance_data_disfa = appearance_data_disfa(valid_inds,:);
+appearance_data_tmp = appearance_data_tmp(valid_inds_tmp,:);
-vid_ids_train_disfa = vid_ids_train_disfa(valid_inds,:);
+vid_ids_train_tmp = vid_ids_train_tmp(valid_inds_tmp,:);
 
-appearance_data = cat(1,appearance_data, appearance_data_disfa);
+appearance_data = cat(1,appearance_data, appearance_data_tmp);
-vid_ids_train = cat(1,vid_ids_train, vid_ids_train_disfa);
+vid_ids_train = cat(1,vid_ids_train, vid_ids_train_tmp);
 
-%% BP4D
+%% BP4D train
-hog_dir = 'D:\Datasets\FERA_2015\bp4d\processed_data/train/';
+hog_dir = [face_processed_dir, '/bp4d/train/'];
-hog_files = dir([hog_dir, '*.hog']);
+hog_files = dir([hog_dir '*.hog']);
+[appearance_data_tmp, valid_inds_tmp, vid_ids_train_tmp] = Read_HOG_files_small(hog_files, hog_dir);
 
-[appearance_data_bp, valid_inds, vid_ids_train_bp] = Read_HOG_files_small(hog_files, hog_dir, 50);
+appearance_data_tmp = appearance_data_tmp(valid_inds_tmp,:);
+vid_ids_train_tmp = vid_ids_train_tmp(valid_inds_tmp,:);
 
-appearance_data_bp = appearance_data_bp(valid_inds,:);
+appearance_data = cat(1,appearance_data, appearance_data_tmp);
-vid_ids_train_bp = vid_ids_train_bp(valid_inds,:);
+vid_ids_train = cat(1,vid_ids_train, vid_ids_train_tmp);
 
-appearance_data = cat(1,appearance_data, appearance_data_bp);
+%% SEMAINE train
-vid_ids_train = cat(1,vid_ids_train, vid_ids_train_bp);
+hog_dir = [face_processed_dir, '/semaine/train/'];
+hog_files = dir([hog_dir '*.hog']);
 
-%% SEMAINE
+[appearance_data_tmp, valid_inds_tmp, vid_ids_train_tmp] = Read_HOG_files_small(hog_files, hog_dir);
-hog_dir = 'D:\Datasets\FERA_2015\semaine\processed_data\train\';
-hog_files = dir([hog_dir, '*.hog']);
 
-[appearance_data_semaine, valid_inds, vid_ids_train_semaine] = Read_HOG_files_small(hog_files, hog_dir, 300);
+appearance_data_tmp = appearance_data_tmp(valid_inds_tmp,:);
+vid_ids_train_tmp = vid_ids_train_tmp(valid_inds_tmp,:);
 
-appearance_data_semaine = appearance_data_semaine(valid_inds,:);
+appearance_data = cat(1,appearance_data, appearance_data_tmp);
-vid_ids_train_semaine = vid_ids_train_semaine(valid_inds,:);
+vid_ids_train = cat(1,vid_ids_train, vid_ids_train_tmp);
-
-appearance_data = cat(1,appearance_data, appearance_data_semaine);
-vid_ids_train = cat(1,vid_ids_train, vid_ids_train_semaine);
 
 %%
 means_norm = mean(appearance_data);

matlab_version/AU_training/pca_generation/createSubFaceModels.m

@@ -1,60 +1,93 @@
 clear;
+face_processed_dir = 'E:\datasets\face_datasets_processed';
 
-%% CK+, FERA2011, and UNBC datasets
+%% CK+
-hog_dir = 'D:\Datasets/face_datasets/hog_aligned_rigid/';
+hog_dir = [face_processed_dir, '/ck+/'];
-hog_files = dir([hog_dir, '*.hog']);
+hog_files = dir([hog_dir '*.hog']);
-
 [appearance_data, valid_inds, vid_ids_train] = Read_HOG_files_small(hog_files, hog_dir);
 appearance_data = appearance_data(valid_inds,:);
 vid_ids_train = vid_ids_train(valid_inds,:);
 
-%% Bosphorus dataset
+%% Bosphorus
-hog_dir = 'D:\Datasets/face_datasets/hog_aligned_rigid_b/';
+hog_dir = [face_processed_dir, '/bosph/'];
-hog_files = dir([hog_dir, '*.hog']);
+hog_files = dir([hog_dir '*.hog']);
 
-[appearance_data_bosph, valid_inds, vid_ids_train_bosph] = Read_HOG_files_small(hog_files, hog_dir);
+% Remove non-frontal
+frontal = true(size(hog_files));
+for i = 1:numel(frontal)
+    if(~isempty(strfind(hog_files(i).name, 'YR')) || ~isempty(strfind(hog_files(i).name, 'PR'))|| ~isempty(strfind(hog_files(i).name, 'CR')))
+        frontal(i) = false;
+    end   
+end
+
+hog_files = hog_files(frontal);
+
+[appearance_data_tmp, valid_inds_tmp, vid_ids_train_tmp] = Read_HOG_files_small(hog_files, hog_dir);
+
+appearance_data_tmp = appearance_data_tmp(valid_inds_tmp,:);
+vid_ids_train_tmp = vid_ids_train_tmp(valid_inds_tmp,:);
+
+appearance_data = cat(1,appearance_data, appearance_data_tmp);
+vid_ids_train = cat(1,vid_ids_train, vid_ids_train_tmp);
+
+%% FERA2011
+hog_dir = [face_processed_dir, '/fera2011/'];
+hog_files = dir([hog_dir '*.hog']);
+[appearance_data_tmp, valid_inds_tmp, vid_ids_train_tmp] = Read_HOG_files_small(hog_files, hog_dir);
+
+ appearance_data_tmp = appearance_data_tmp(valid_inds_tmp,:);
+vid_ids_train_tmp = vid_ids_train_tmp(valid_inds_tmp,:);
+
+appearance_data = cat(1,appearance_data, appearance_data_tmp);
+vid_ids_train = cat(1,vid_ids_train, vid_ids_train_tmp);
+
+%% UNBC
+hog_dir = [face_processed_dir, '/unbc/'];
+hog_files = dir([hog_dir '*.hog']);
+[appearance_data_tmp, valid_inds_tmp, vid_ids_train_tmp] = Read_HOG_files_small(hog_files, hog_dir);
+
+appearance_data_tmp = appearance_data_tmp(valid_inds_tmp,:);
+vid_ids_train_tmp = vid_ids_train_tmp(valid_inds_tmp,:);
+
+appearance_data = cat(1,appearance_data, appearance_data_tmp);
+vid_ids_train = cat(1,vid_ids_train, vid_ids_train_tmp);
 
-appearance_data_bosph = appearance_data_bosph(valid_inds,:);
-vid_ids_train_bosph = vid_ids_train_bosph(valid_inds,:);
 
-appearance_data = cat(1,appearance_data, appearance_data_bosph);
-vid_ids_train = cat(1,vid_ids_train, vid_ids_train_bosph);
 
 %% DISFA
-hog_dir = 'D:\Datasets\DISFA\hog_aligned_rigid/';
+hog_dir = [face_processed_dir, '/disfa/'];
-hog_files = dir([hog_dir, '*.hog']);
+hog_files = dir([hog_dir '*.hog']);
 
-[appearance_data_disfa, valid_inds, vid_ids_train_disfa] = Read_HOG_files_small(hog_files, hog_dir, 100);
+[appearance_data_tmp, valid_inds_tmp, vid_ids_train_tmp] = Read_HOG_files_small(hog_files, hog_dir);
 
-appearance_data_disfa = appearance_data_disfa(valid_inds,:);
+appearance_data_tmp = appearance_data_tmp(valid_inds_tmp,:);
-vid_ids_train_disfa = vid_ids_train_disfa(valid_inds,:);
+vid_ids_train_tmp = vid_ids_train_tmp(valid_inds_tmp,:);
 
-appearance_data = cat(1,appearance_data, appearance_data_disfa);
+appearance_data = cat(1,appearance_data, appearance_data_tmp);
-vid_ids_train = cat(1,vid_ids_train, vid_ids_train_disfa);
+vid_ids_train = cat(1,vid_ids_train, vid_ids_train_tmp);
 
-%% BP4D
+%% BP4D train
-hog_dir = 'D:\Datasets\FERA_2015\bp4d\processed_data/train/';
+hog_dir = [face_processed_dir, '/bp4d/train/'];
-hog_files = dir([hog_dir, '*.hog']);
+hog_files = dir([hog_dir '*.hog']);
+[appearance_data_tmp, valid_inds_tmp, vid_ids_train_tmp] = Read_HOG_files_small(hog_files, hog_dir);
 
-[appearance_data_bp, valid_inds, vid_ids_train_bp] = Read_HOG_files_small(hog_files, hog_dir, 50);
+appearance_data_tmp = appearance_data_tmp(valid_inds_tmp,:);
+vid_ids_train_tmp = vid_ids_train_tmp(valid_inds_tmp,:);
 
-appearance_data_bp = appearance_data_bp(valid_inds,:);
+appearance_data = cat(1,appearance_data, appearance_data_tmp);
-vid_ids_train_bp = vid_ids_train_bp(valid_inds,:);
+vid_ids_train = cat(1,vid_ids_train, vid_ids_train_tmp);
 
-appearance_data = cat(1,appearance_data, appearance_data_bp);
+%% SEMAINE train
-vid_ids_train = cat(1,vid_ids_train, vid_ids_train_bp);
+hog_dir = [face_processed_dir, '/semaine/train/'];
+hog_files = dir([hog_dir '*.hog']);
 
-%% SEMAINE
+[appearance_data_tmp, valid_inds_tmp, vid_ids_train_tmp] = Read_HOG_files_small(hog_files, hog_dir);
-hog_dir = 'D:\Datasets\FERA_2015\semaine\processed_data\train\';
-hog_files = dir([hog_dir, '*.hog']);
 
-[appearance_data_semaine, valid_inds, vid_ids_train_semaine] = Read_HOG_files_small(hog_files, hog_dir, 300);
+appearance_data_tmp = appearance_data_tmp(valid_inds_tmp,:);
+vid_ids_train_tmp = vid_ids_train_tmp(valid_inds_tmp,:);
 
-appearance_data_semaine = appearance_data_semaine(valid_inds,:);
+appearance_data = cat(1,appearance_data, appearance_data_tmp);
-vid_ids_train_semaine = vid_ids_train_semaine(valid_inds,:);
+vid_ids_train = cat(1,vid_ids_train, vid_ids_train_tmp);
-
-appearance_data = cat(1,appearance_data, appearance_data_semaine);
-vid_ids_train = cat(1,vid_ids_train, vid_ids_train_semaine);
 
 %%
 means_norm = mean(appearance_data);