ROI reinitialization, preference for large faces.

gui/OpenFaceDemo/MainWindow.xaml

@@ -6,7 +6,7 @@
         xmlns:local="clr-namespace:OpenFaceDemo"
         xmlns:of="clr-namespace:OpenFaceOffline;assembly=OpenFaceOffline"
         mc:Ignorable="d"
-        Title="OpenFace Analyser" Height="800" Width="1300" MinWidth="700" MinHeight="450" Closing="Window_Closing" WindowStartupLocation="CenterScreen">
+        Title="OpenFace Analyser" Height="800" Width="1300" MinWidth="700" MinHeight="450" Closing="Window_Closing" WindowStartupLocation="CenterScreen" KeyDown="Window_KeyDown">
     <Grid Name="MainGrid" Margin="-1,1,1.333,-1.333">
         <Grid.ColumnDefinitions>
             <ColumnDefinition Width="1.8*"/>
@@ -27,8 +27,8 @@
                 </MenuItem>
             </MenuItem>
         </Menu>
-        <Border Name="VideoBorder" Grid.Row="1" Grid.Column="0" Grid.ColumnSpan="2" Grid.RowSpan="3" BorderBrush="Black" BorderThickness="1" Background="LightGray" Margin="5,5,0,0">
+        <Border Name="VideoBorder" Grid.Row="1" Grid.Column="0" Grid.ColumnSpan="2" Grid.RowSpan="3" BorderBrush="Black" BorderThickness="1" Background="LightGray" Margin="5,5,0,0" >
-            <of:OverlayImage x:Name="video" />
+            <of:OverlayImage x:Name="video" MouseDown="video_MouseDown" />
         </Border>
 
         <local:AxesTimeSeriesPlot NumVertGrid="5" x:Name="headPosePlot" ShowLegend="True" MinVal="-1" MaxVal="1" MinHeight="180" Grid.Row="4" Grid.Column="0" Padding="60 20 30 40" RangeLabel="Head pose" Orientation="Horizontal">

gui/OpenFaceDemo/MainWindow.xaml.cs

@@ -62,8 +62,10 @@ namespace OpenFaceDemo
         
         FpsTracker processing_fps = new FpsTracker();
 
+        // Controlling the model reset
         volatile bool detectionSucceeding = false;
         volatile bool reset = false;
+        Point? resetPoint = null;
 
         // For selecting webcams
         CameraSelection cam_sec;
@@ -73,6 +75,7 @@ namespace OpenFaceDemo
         CLNF clnf_model;
         FaceAnalyserManaged face_analyser;
 
+
         public MainWindow()
         {
             InitializeComponent();
@@ -245,7 +248,7 @@ namespace OpenFaceDemo
                     cx = grayFrame.Width / 2f;
                     cy = grayFrame.Height / 2f;
                 }
-
+                
                 bool detectionSucceeding = ProcessFrame(clnf_model, clnf_params, frame, grayFrame, fx, fy, cx, cy);
 
                 double confidence = (-clnf_model.GetConfidence()) / 2.0 + 0.5;
@@ -384,7 +387,16 @@ namespace OpenFaceDemo
 
                 if (reset)
                 {
-                    clnf_model.Reset();
+                    if (resetPoint.HasValue)
+                    {
+                        clnf_model.Reset(resetPoint.Value.X, resetPoint.Value.Y);
+                        resetPoint = null;
+                    }
+                    else
+                    {
+                        clnf_model.Reset();
+                    }
+
                     face_analyser.Reset();
                     reset = false;
 
@@ -477,13 +489,32 @@ namespace OpenFaceDemo
                 thread_running = false;
                 processing_thread.Join();
 
-                capture.Dispose();
+                if (capture != null)
+                    capture.Dispose();
+                
             }
-            
+            if (face_analyser != null)
-            face_analyser.Dispose();
+                face_analyser.Dispose();
-            clnf_model.Dispose();
+            if(clnf_model != null)
-            this.Close();
+                clnf_model.Dispose();
+
         }
 
+        private void Window_KeyDown(object sender, KeyEventArgs e)
+        {
+            if (e.Key == Key.R)
+            {
+                reset = true;
+            }
+        }
+
+        private void video_MouseDown(object sender, MouseButtonEventArgs e)
+        {
+            var clickPos = e.GetPosition(video);
+            resetPoint = new Point(clickPos.X / video.ActualWidth, clickPos.Y / video.ActualHeight);
+            reset = true;
+        }
+
+
     }
 }

lib/local/LandmarkDetector/src/LandmarkDetectorModel.cpp

@@ -548,6 +548,9 @@ void CLNF::Read(string main_location)
 
 	failures_in_a_row = -1;
 
+	preference_det.x = -1;
+	preference_det.y = -1;
+
 }
 
 // Resetting the model (for a new video, or complet reinitialisation

lib/local/LandmarkDetector/src/LandmarkDetectorUtils.cpp

@@ -1452,9 +1452,11 @@ bool DetectSingleFaceHOG(cv::Rect_<double>& o_region, const cv::Mat_<uchar>& int
 	// The tracker can return multiple faces
 	vector<cv::Rect_<double> > face_detections;
 	vector<double> confidences;
-
 	bool detect_success = LandmarkDetector::DetectFacesHOG(face_detections, intensity_img, detector, confidences);
-					
+
+	// In case of multiple faces pick the biggest one
+	bool use_size = true;
+
 	if(detect_success)
 	{
 
@@ -1463,10 +1465,14 @@ bool DetectSingleFaceHOG(cv::Rect_<double>& o_region, const cv::Mat_<uchar>& int
 		// keep the most confident one or the one closest to preference point if set
 		double best_so_far;
 		if(use_preferred)
-		{			
+		{					
 			best_so_far = sqrt((preference.x - (face_detections[0].width/2 + face_detections[0].x)) * (preference.x - (face_detections[0].width/2 + face_detections[0].x)) + 
 							   (preference.y - (face_detections[0].height/2 + face_detections[0].y)) * (preference.y - (face_detections[0].height/2 + face_detections[0].y)));
 		}
+		else if (use_size)
+		{
+			best_so_far = (face_detections[0].width + face_detections[0].height) / 2.0;
+		}
 		else
 		{
 			best_so_far = confidences[0];
@@ -1481,10 +1487,16 @@ bool DetectSingleFaceHOG(cv::Rect_<double>& o_region, const cv::Mat_<uchar>& int
 
 			if(use_preferred)
 			{
-				dist = sqrt((preference.x - (face_detections[0].width/2 + face_detections[0].x)) * (preference.x - (face_detections[0].width/2 + face_detections[0].x)) + 
+				dist = sqrt((preference.x - (face_detections[i].width/2 + face_detections[i].x)) * (preference.x - (face_detections[i].width/2 + face_detections[i].x)) + 
-							   (preference.y - (face_detections[0].height/2 + face_detections[0].y)) * (preference.y - (face_detections[0].height/2 + face_detections[0].y)));
+							   (preference.y - (face_detections[i].height/2 + face_detections[i].y)) * (preference.y - (face_detections[i].height/2 + face_detections[i].y)));
+
 				better = dist < best_so_far;
 			}
+			else if (use_size)
+			{
+				dist = (face_detections[i].width + face_detections[i].height) / 2.0;
+				better = dist > best_so_far;
+			}
 			else
 			{
 				dist = confidences[i];