AU training code adaptation to the new interface and testing.

matlab_runners/Action Unit Experiments/results/BP4D_valid_res_class.txt

@@ -1,11 +1,11 @@
-AU1 class, Precision - 0.555, Recall - 0.533, F1 - 0.544
+AU1 class, Precision - 0.538, Recall - 0.532, F1 - 0.535
-AU2 class, Precision - 0.403, Recall - 0.439, F1 - 0.420
+AU2 class, Precision - 0.400, Recall - 0.454, F1 - 0.425
-AU4 class, Precision - 0.491, Recall - 0.513, F1 - 0.502
+AU4 class, Precision - 0.478, Recall - 0.516, F1 - 0.497
-AU6 class, Precision - 0.741, Recall - 0.776, F1 - 0.758
+AU6 class, Precision - 0.742, Recall - 0.769, F1 - 0.755
-AU7 class, Precision - 0.764, Recall - 0.727, F1 - 0.745
+AU7 class, Precision - 0.760, Recall - 0.745, F1 - 0.753
-AU10 class, Precision - 0.849, Recall - 0.840, F1 - 0.845
+AU10 class, Precision - 0.840, Recall - 0.851, F1 - 0.845
-AU12 class, Precision - 0.887, Recall - 0.820, F1 - 0.852
+AU12 class, Precision - 0.890, Recall - 0.816, F1 - 0.851
-AU14 class, Precision - 0.542, Recall - 0.807, F1 - 0.649
+AU14 class, Precision - 0.567, Recall - 0.803, F1 - 0.665
-AU15 class, Precision - 0.402, Recall - 0.417, F1 - 0.409
+AU15 class, Precision - 0.362, Recall - 0.406, F1 - 0.382
-AU17 class, Precision - 0.631, Recall - 0.596, F1 - 0.613
+AU17 class, Precision - 0.623, Recall - 0.588, F1 - 0.605
-AU23 class, Precision - 0.335, Recall - 0.598, F1 - 0.429
+AU23 class, Precision - 0.331, Recall - 0.552, F1 - 0.414

matlab_runners/Action Unit Experiments/results/BP4D_valid_res_int.txt

@@ -1,5 +1,5 @@
-AU6 results - rms 0.858, corr 0.786, ccc - 0.737
+AU6 results - rms 0.869, corr 0.777, ccc - 0.730
-AU10 results - rms 1.044, corr 0.736, ccc - 0.678
+AU10 results - rms 1.024, corr 0.735, ccc - 0.694
-AU12 results - rms 0.828, corr 0.865, ccc - 0.827
+AU12 results - rms 0.819, corr 0.862, ccc - 0.833
-AU14 results - rms 1.104, corr 0.532, ccc - 0.485
+AU14 results - rms 1.123, corr 0.537, ccc - 0.492
-AU17 results - rms 0.833, corr 0.591, ccc - 0.490
+AU17 results - rms 0.842, corr 0.582, ccc - 0.476

matlab_runners/Action Unit Experiments/results/Bosphorus_res_class.txt

@@ -1,17 +1,17 @@
-AU1 class, Precision - 0.434, Recall - 0.673, F1 - 0.528
+AU1 class, Precision - 0.417, Recall - 0.834, F1 - 0.556
-AU2 class, Precision - 0.298, Recall - 0.818, F1 - 0.437
+AU2 class, Precision - 0.313, Recall - 0.816, F1 - 0.453
-AU4 class, Precision - 0.564, Recall - 0.861, F1 - 0.681
+AU4 class, Precision - 0.536, Recall - 0.856, F1 - 0.659
-AU5 class, Precision - 0.387, Recall - 0.915, F1 - 0.544
+AU5 class, Precision - 0.419, Recall - 0.958, F1 - 0.583
-AU6 class, Precision - 0.355, Recall - 0.811, F1 - 0.494
+AU6 class, Precision - 0.354, Recall - 0.804, F1 - 0.492
-AU7 class, Precision - 0.778, Recall - 0.783, F1 - 0.780
+AU7 class, Precision - 0.812, Recall - 0.783, F1 - 0.798
-AU9 class, Precision - 0.370, Recall - 0.953, F1 - 0.533
+AU9 class, Precision - 0.410, Recall - 0.953, F1 - 0.574
-AU10 class, Precision - 0.340, Recall - 0.788, F1 - 0.475
+AU10 class, Precision - 0.336, Recall - 0.788, F1 - 0.471
-AU12 class, Precision - 0.690, Recall - 0.842, F1 - 0.758
+AU12 class, Precision - 0.702, Recall - 0.873, F1 - 0.778
-AU14 class, Precision - 0.185, Recall - 0.881, F1 - 0.305
+AU14 class, Precision - 0.189, Recall - 0.854, F1 - 0.309
-AU15 class, Precision - 0.171, Recall - 0.851, F1 - 0.285
+AU15 class, Precision - 0.178, Recall - 0.879, F1 - 0.296
-AU17 class, Precision - 0.309, Recall - 0.861, F1 - 0.455
+AU17 class, Precision - 0.303, Recall - 0.864, F1 - 0.449
-AU20 class, Precision - 0.130, Recall - 0.921, F1 - 0.228
+AU20 class, Precision - 0.129, Recall - 0.956, F1 - 0.228
-AU23 class, Precision - 0.104, Recall - 0.837, F1 - 0.186
+AU23 class, Precision - 0.102, Recall - 0.830, F1 - 0.182
-AU25 class, Precision - 0.869, Recall - 0.860, F1 - 0.865
+AU25 class, Precision - 0.883, Recall - 0.900, F1 - 0.892
-AU26 class, Precision - 0.368, Recall - 0.809, F1 - 0.506
+AU26 class, Precision - 0.383, Recall - 0.800, F1 - 0.518
-AU45 class, Precision - 0.367, Recall - 0.754, F1 - 0.494
+AU45 class, Precision - 0.374, Recall - 0.765, F1 - 0.502

matlab_runners/Action Unit Experiments/results/Bosphorus_res_int.txt

@@ -1,17 +1,17 @@
-AU1 intensity, Corr - 0.712, RMS - 0.925, CCC - 0.652
+AU1 intensity, Corr - 0.733, RMS - 0.898, CCC - 0.672
-AU2 intensity, Corr - 0.696, RMS - 0.772, CCC - 0.626
+AU2 intensity, Corr - 0.721, RMS - 0.750, CCC - 0.645
-AU4 intensity, Corr - 0.797, RMS - 0.623, CCC - 0.764
+AU4 intensity, Corr - 0.799, RMS - 0.621, CCC - 0.764
-AU5 intensity, Corr - 0.767, RMS - 0.740, CCC - 0.694
+AU5 intensity, Corr - 0.790, RMS - 0.717, CCC - 0.719
-AU6 intensity, Corr - 0.541, RMS - 0.786, CCC - 0.506
+AU6 intensity, Corr - 0.552, RMS - 0.773, CCC - 0.519
-AU7 intensity, Corr - 0.830, RMS - 0.750, CCC - 0.811
+AU7 intensity, Corr - 0.868, RMS - 0.670, CCC - 0.848
-AU9 intensity, Corr - 0.763, RMS - 0.611, CCC - 0.701
+AU9 intensity, Corr - 0.798, RMS - 0.590, CCC - 0.737
-AU10 intensity, Corr - 0.491, RMS - 0.759, CCC - 0.461
+AU10 intensity, Corr - 0.480, RMS - 0.789, CCC - 0.444
-AU12 intensity, Corr - 0.804, RMS - 0.715, CCC - 0.766
+AU12 intensity, Corr - 0.822, RMS - 0.687, CCC - 0.784
-AU14 intensity, Corr - 0.357, RMS - 0.931, CCC - 0.277
+AU14 intensity, Corr - 0.359, RMS - 0.946, CCC - 0.273
-AU15 intensity, Corr - 0.516, RMS - 0.565, CCC - 0.431
+AU15 intensity, Corr - 0.535, RMS - 0.671, CCC - 0.427
-AU17 intensity, Corr - 0.554, RMS - 0.893, CCC - 0.477
+AU17 intensity, Corr - 0.576, RMS - 0.911, CCC - 0.494
-AU20 intensity, Corr - 0.411, RMS - 0.901, CCC - 0.277
+AU20 intensity, Corr - 0.437, RMS - 0.910, CCC - 0.286
-AU23 intensity, Corr - 0.351, RMS - 0.736, CCC - 0.274
+AU23 intensity, Corr - 0.330, RMS - 0.713, CCC - 0.225
-AU25 intensity, Corr - 0.846, RMS - 0.809, CCC - 0.822
+AU25 intensity, Corr - 0.864, RMS - 0.772, CCC - 0.837
-AU26 intensity, Corr - 0.516, RMS - 0.995, CCC - 0.453
+AU26 intensity, Corr - 0.557, RMS - 0.964, CCC - 0.490
-AU45 intensity, Corr - 0.840, RMS - 0.662, CCC - 0.791
+AU45 intensity, Corr - 0.853, RMS - 0.659, CCC - 0.794

matlab_runners/Action Unit Experiments/results/DISFA_valid_res.txt

@@ -1,12 +1,12 @@
-AU1 results - corr 0.826, rms 0.412, ccc - 0.803
+AU1 results - corr 0.831, rms 0.407, ccc - 0.802
-AU2 results - corr 0.763, rms 0.445, ccc - 0.656
+AU2 results - corr 0.717, rms 0.481, ccc - 0.582
-AU4 results - corr 0.874, rms 0.565, ccc - 0.848
+AU4 results - corr 0.873, rms 0.568, ccc - 0.846
-AU5 results - corr 0.745, rms 0.181, ccc - 0.711
+AU5 results - corr 0.741, rms 0.182, ccc - 0.712
-AU6 results - corr 0.706, rms 0.592, ccc - 0.665
+AU6 results - corr 0.696, rms 0.612, ccc - 0.651
-AU9 results - corr 0.740, rms 0.385, ccc - 0.687
+AU9 results - corr 0.744, rms 0.383, ccc - 0.679
-AU12 results - corr 0.869, rms 0.494, ccc - 0.856
+AU12 results - corr 0.872, rms 0.493, ccc - 0.858
-AU15 results - corr 0.745, rms 0.269, ccc - 0.712
+AU15 results - corr 0.747, rms 0.274, ccc - 0.718
-AU17 results - corr 0.642, rms 0.517, ccc - 0.574
+AU17 results - corr 0.636, rms 0.519, ccc - 0.566
-AU20 results - corr 0.619, rms 0.311, ccc - 0.581
+AU20 results - corr 0.640, rms 0.302, ccc - 0.595
-AU25 results - corr 0.926, rms 0.500, ccc - 0.920
+AU25 results - corr 0.924, rms 0.507, ccc - 0.917
-AU26 results - corr 0.802, rms 0.449, ccc - 0.762
+AU26 results - corr 0.802, rms 0.448, ccc - 0.772

matlab_runners/Action Unit Experiments/results/FERA2011_res_class.txt

@@ -1,11 +1,11 @@
-AU1 class, Precision - 0.587, Recall - 0.720, F1 - 0.647
+AU1 class, Precision - 0.506, Recall - 0.820, F1 - 0.626
-AU2 class, Precision - 0.470, Recall - 0.797, F1 - 0.591
+AU2 class, Precision - 0.471, Recall - 0.744, F1 - 0.577
-AU4 class, Precision - 0.499, Recall - 0.753, F1 - 0.600
+AU4 class, Precision - 0.482, Recall - 0.755, F1 - 0.588
-AU6 class, Precision - 0.836, Recall - 0.674, F1 - 0.746
+AU6 class, Precision - 0.777, Recall - 0.685, F1 - 0.728
-AU7 class, Precision - 0.683, Recall - 0.791, F1 - 0.733
+AU7 class, Precision - 0.672, Recall - 0.778, F1 - 0.721
-AU10 class, Precision - 0.524, Recall - 0.748, F1 - 0.616
+AU10 class, Precision - 0.508, Recall - 0.751, F1 - 0.606
-AU12 class, Precision - 0.919, Recall - 0.659, F1 - 0.768
+AU12 class, Precision - 0.885, Recall - 0.698, F1 - 0.781
-AU15 class, Precision - 0.358, Recall - 0.639, F1 - 0.459
+AU15 class, Precision - 0.323, Recall - 0.664, F1 - 0.434
-AU17 class, Precision - 0.229, Recall - 0.287, F1 - 0.255
+AU17 class, Precision - 0.243, Recall - 0.318, F1 - 0.275
-AU25 class, Precision - 0.205, Recall - 0.869, F1 - 0.332
+AU25 class, Precision - 0.206, Recall - 0.892, F1 - 0.335
-AU26 class, Precision - 0.122, Recall - 0.972, F1 - 0.216
+AU26 class, Precision - 0.126, Recall - 0.974, F1 - 0.222

matlab_runners/Action Unit Experiments/results/SEMAINE_valid_res.txt

@@ -1,6 +1,6 @@
-AU2 class, Precision - 0.361, Recall - 0.746, F1 - 0.486
+AU2 class, Precision - 0.344, Recall - 0.752, F1 - 0.472
-AU12 class, Precision - 0.424, Recall - 0.781, F1 - 0.550
+AU12 class, Precision - 0.430, Recall - 0.783, F1 - 0.555
-AU17 class, Precision - 0.110, Recall - 0.812, F1 - 0.194
+AU17 class, Precision - 0.111, Recall - 0.857, F1 - 0.196
-AU25 class, Precision - 0.338, Recall - 0.525, F1 - 0.411
+AU25 class, Precision - 0.335, Recall - 0.520, F1 - 0.408
-AU28 class, Precision - 0.432, Recall - 0.475, F1 - 0.453
+AU28 class, Precision - 0.393, Recall - 0.475, F1 - 0.430
-AU45 class, Precision - 0.295, Recall - 0.615, F1 - 0.399
+AU45 class, Precision - 0.310, Recall - 0.591, F1 - 0.406

matlab_runners/Feature Point Experiments/results/fps_yt.txt

@@ -1,3 +1,3 @@
 Model, mean,  median
 OpenFace (CLNF):  0.0564,   0.0515
-CLM:   0.0630,   0.0586
+CLM:   0.0631,   0.0587

matlab_runners/Gaze Experiments/mpii_1500_errs.txt

@@ -1,2 +1,2 @@
 Mean error, median error
-9.431, 8.611
+9.428, 8.611

matlab_runners/Head Pose Experiments/results/Pose_OF.txt

@@ -1,4 +1,4 @@
 Dataset and model,        pitch,  yaw,  roll,  mean,  median
-biwi error:  6.981,   5.174, 4.571,  5.575,  2.612
+biwi error:  7.091,   5.170, 4.657,  5.639,  2.609
-bu error:    2.738,   3.349, 2.459,  2.849,  1.975
+bu error:    2.739,   3.349, 2.459,  2.849,  1.974
-ict error:   3.497,   3.985, 3.298,  3.593,  1.965
+ict error:   3.498,   3.986, 3.298,  3.594,  1.966

matlab_version/AU_training/data extraction/extract_FERA2011_labels.m

@@ -18,7 +18,20 @@ function [ labels, valid_ids, filenames  ] = extract_FERA2011_labels( FERA2011_d
         [~, filename,~] = fileparts(file);
         filenames{file_id} = filename;
 
-        data = csvread(file); %import annotations for one video file
+        delimiter = {'   '};
+        formatSpec = '%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%f%[^\n\r]';
+
+        %% Open the text file.
+        fileID = fopen(file,'r');
+
+        %% Read columns of data according to the format.
+        data = textscan(fileID, formatSpec, 'Delimiter', delimiter, 'MultipleDelimsAsOne', true, 'TextType', 'string',  'ReturnOnError', false);
+        data = [data{1:end-1}];
+
+        %% Close the text file.
+        fclose(fileID);
+
+        %data = dlmread(file, ' '); %import annotations for one video file
        
         speech = data(:,end);
 

matlab_version/AU_training/data extraction/extract_features_FERA_2011.m

@@ -26,8 +26,9 @@ parfor f1=1:numel(fera_dirs)
         for v=1:numel(vid_files)
             
             input_file = [FERA2011_dir, fera_dirs(f1).name, '/', fera_dirs_level_2(f2).name, '/', vid_files(v).name];
-            
+            [~, name, ~] = fileparts(vid_files(v).name);
-            command = sprintf('%s -f "%s" -out_dir "%s" -hogalign -pdmparams', features_exe, input_file, output_dir );
+            out_name = [fera_dirs(f1).name '_' name];
+            command = sprintf('%s -f "%s" -out_dir "%s" -hogalign -pdmparams -of %s', features_exe, input_file, output_dir, out_name );
 
             dos(command);
             

matlab_version/AU_training/data extraction/extract_features_SEMAINE.m

@@ -24,7 +24,7 @@ parfor f1=1:numel(semaine_dirs)
 
             input_file = [SEMAINE_dir, f1_dir, '/', vid_files(v).name];
 
-            command = sprintf('%s -f "%s" -out_dir "%s" -hogalign -pdmparams', features_exe, input_file, output_dir );
+            command = sprintf('%s -f "%s" -out_dir "%s" -hogalign -pdmparams -of %s', features_exe, input_file, output_dir, f1_dir );
 
             dos(command);
         end
@@ -47,7 +47,7 @@ parfor f1=1:numel(semaine_dirs)
 
             input_file = [SEMAINE_dir, f1_dir, '/', vid_files(v).name];
 
-            command = sprintf('%s -f "%s" -out_dir "%s" -hogalign -pdmparams', features_exe, input_file, output_dir );
+            command = sprintf('%s -f "%s" -out_dir "%s" -hogalign -pdmparams -of %s', features_exe, input_file, output_dir, f1_dir );
 
             dos(command);
 

matlab_version/AU_training/data extraction/find_SEMAINE.m

@@ -15,7 +15,7 @@ else
 end
 
 if(exist('SEMAINE_dir', 'var'))
-    hog_data_dir = [SEMAINE_dir, '../processed_data/'];
+    hog_data_dir = 'E:\datasets\face_datasets_processed\semaine/';
 end
 
 train_recs = {'rec1', 'rec12', 'rec14', 'rec19', 'rec23', 'rec25', 'rec37', 'rec39', 'rec43', 'rec45', 'rec48', 'rec50', 'rec52', 'rec54', 'rec56', 'rec60'};