// The main function call for processing the webcam feed
private void ProcessingLoop(SequenceReader reader)
{
thread_running = true;
Thread.CurrentThread.IsBackground = true;
DateTime?startTime = CurrentTime;
var lastFrameTime = CurrentTime;
landmark_detector.Reset();
face_analyser.Reset();
int frame_id = 0;
double old_gaze_x = 0;
double old_gaze_y = 0;
double smile_cumm = 0;
double frown_cumm = 0;
double brow_up_cumm = 0;
double brow_down_cumm = 0;
double widen_cumm = 0;
double wrinkle_cumm = 0;
while (thread_running)
{
// Loading an image file
RawImage frame = new RawImage(reader.GetNextImage());
RawImage gray_frame = new RawImage(reader.GetCurrentFrameGray());
lastFrameTime = CurrentTime;
processing_fps.AddFrame();
bool detection_succeeding = landmark_detector.DetectLandmarksInVideo(gray_frame, face_model_params);
// The face analysis step (only done if recording AUs, HOGs or video)
face_analyser.AddNextFrame(frame, landmark_detector.CalculateAllLandmarks(), detection_succeeding, true);
gaze_analyser.AddNextFrame(landmark_detector, detection_succeeding, reader.GetFx(), reader.GetFy(), reader.GetCx(), reader.GetCy());
double confidence = landmark_detector.GetConfidence();
if (confidence < 0)
{
confidence = 0;
}
else if (confidence > 1)
{
confidence = 1;
}
List <double> pose = new List <double>();
landmark_detector.GetPose(pose, reader.GetFx(), reader.GetFy(), reader.GetCx(), reader.GetCy());
List <double> non_rigid_params = landmark_detector.GetNonRigidParams();
double scale = landmark_detector.GetRigidParams()[0];
double time_stamp = (DateTime.Now - (DateTime)startTime).TotalMilliseconds;
List <Tuple <Point, Point> > lines = null;
List <Tuple <double, double> > landmarks = null;
List <Tuple <double, double> > eye_landmarks = null;
List <Tuple <Point, Point> > gaze_lines = null;
Tuple <double, double> gaze_angle = gaze_analyser.GetGazeAngle();
if (detection_succeeding)
{
landmarks = landmark_detector.CalculateVisibleLandmarks();
eye_landmarks = landmark_detector.CalculateVisibleEyeLandmarks();
lines = landmark_detector.CalculateBox(reader.GetFx(), reader.GetFy(), reader.GetCx(), reader.GetCy());
gaze_lines = gaze_analyser.CalculateGazeLines(reader.GetFx(), reader.GetFy(), reader.GetCx(), reader.GetCy());
}
// Visualisation
Dispatcher.Invoke(DispatcherPriority.Render, new TimeSpan(0, 0, 0, 0, 200), (Action)(() =>
{
var au_regs = face_analyser.GetCurrentAUsReg();
if (au_regs.Count > 0)
{
double smile = (au_regs["AU12"] + au_regs["AU06"] + au_regs["AU25"]) / 13.0;
double frown = (au_regs["AU15"] + au_regs["AU17"]) / 12.0;
double brow_up = (au_regs["AU01"] + au_regs["AU02"]) / 10.0;
double brow_down = au_regs["AU04"] / 5.0;
double eye_widen = au_regs["AU05"] / 3.0;
double nose_wrinkle = au_regs["AU09"] / 4.0;
Dictionary <int, double> smileDict = new Dictionary <int, double>();
smileDict[0] = 0.7 * smile_cumm + 0.3 * smile;
smileDict[1] = 0.7 * frown_cumm + 0.3 * frown;
smilePlot.AddDataPoint(new DataPointGraph()
{
Time = CurrentTime, values = smileDict, Confidence = confidence
});
Dictionary <int, double> browDict = new Dictionary <int, double>();
browDict[0] = 0.7 * brow_up_cumm + 0.3 * brow_up;
browDict[1] = 0.7 * brow_down_cumm + 0.3 * brow_down;
browPlot.AddDataPoint(new DataPointGraph()
{
Time = CurrentTime, values = browDict, Confidence = confidence
});
Dictionary <int, double> eyeDict = new Dictionary <int, double>();
eyeDict[0] = 0.7 * widen_cumm + 0.3 * eye_widen;
eyeDict[1] = 0.7 * wrinkle_cumm + 0.3 * nose_wrinkle;
eyePlot.AddDataPoint(new DataPointGraph()
{
Time = CurrentTime, values = eyeDict, Confidence = confidence
});
smile_cumm = smileDict[0];
frown_cumm = smileDict[1];
brow_up_cumm = browDict[0];
brow_down_cumm = browDict[1];
widen_cumm = eyeDict[0];
wrinkle_cumm = eyeDict[1];
}
else
{
// If no AUs present disable the AU visualization
MainGrid.ColumnDefinitions[2].Width = new GridLength(0);
eyePlot.Visibility = Visibility.Collapsed;
browPlot.Visibility = Visibility.Collapsed;
smilePlot.Visibility = Visibility.Collapsed;
}
Dictionary <int, double> poseDict = new Dictionary <int, double>();
poseDict[0] = -pose[3];
poseDict[1] = pose[4];
poseDict[2] = pose[5];
headPosePlot.AddDataPoint(new DataPointGraph()
{
Time = CurrentTime, values = poseDict, Confidence = confidence
});
Dictionary <int, double> gazeDict = new Dictionary <int, double>();
gazeDict[0] = gaze_angle.Item1 * (180.0 / Math.PI);
gazeDict[0] = 0.5 * old_gaze_x + 0.5 * gazeDict[0];
gazeDict[1] = -gaze_angle.Item2 * (180.0 / Math.PI);
gazeDict[1] = 0.5 * old_gaze_y + 0.5 * gazeDict[1];
gazePlot.AddDataPoint(new DataPointGraph()
{
Time = CurrentTime, values = gazeDict, Confidence = confidence
});
old_gaze_x = gazeDict[0];
old_gaze_y = gazeDict[1];
if (latest_img == null)
{
latest_img = frame.CreateWriteableBitmap();
}
frame.UpdateWriteableBitmap(latest_img);
video.Source = latest_img;
video.Confidence = confidence;
video.FPS = processing_fps.GetFPS();
if (!detection_succeeding)
{
video.OverlayLines.Clear();
video.OverlayPoints.Clear();
video.OverlayEyePoints.Clear();
video.GazeLines.Clear();
}
else
{
video.OverlayLines = lines;
List <Point> landmark_points = new List <Point>();
foreach (var p in landmarks)
{
landmark_points.Add(new Point(p.Item1, p.Item2));
}
List <Point> eye_landmark_points = new List <Point>();
foreach (var p in eye_landmarks)
{
eye_landmark_points.Add(new Point(p.Item1, p.Item2));
}
video.OverlayPoints = landmark_points;
video.OverlayEyePoints = eye_landmark_points;
video.GazeLines = gaze_lines;
}
}));
if (reset)
{
if (resetPoint.HasValue)
{
landmark_detector.Reset(resetPoint.Value.X, resetPoint.Value.Y);
resetPoint = null;
}
else
{
landmark_detector.Reset();
}
face_analyser.Reset();
reset = false;
Dispatcher.Invoke(DispatcherPriority.Render, new TimeSpan(0, 0, 0, 0, 200), (Action)(() =>
{
headPosePlot.ClearDataPoints();
headPosePlot.ClearDataPoints();
gazePlot.ClearDataPoints();
smilePlot.ClearDataPoints();
browPlot.ClearDataPoints();
eyePlot.ClearDataPoints();
}));
}
frame_id++;
}
reader.Close();
latest_img = null;
}
private void VisualizeFeatures(RawImage frame, Visualizer visualizer, List <Tuple <float, float> > landmarks, List <bool> visibilities, bool detection_succeeding,
bool new_image, bool multi_face, float fx, float fy, float cx, float cy, double progress)
{
List <Tuple <Point, Point> > lines = null;
List <Tuple <float, float> > eye_landmarks = null;
List <Tuple <Point, Point> > gaze_lines = null;
Tuple <float, float> gaze_angle = new Tuple <float, float>(0, 0);
List <float> pose = new List <float>();
landmark_detector.GetPose(pose, fx, fy, cx, cy);
List <float> non_rigid_params = landmark_detector.GetNonRigidParams();
double confidence = landmark_detector.GetConfidence();
if (confidence < 0)
{
confidence = 0;
}
else if (confidence > 1)
{
confidence = 1;
}
double scale = landmark_detector.GetRigidParams()[0];
// Helps with recording and showing the visualizations
if (new_image)
{
visualizer.SetImage(frame, fx, fy, cx, cy);
}
visualizer.SetObservationHOG(face_analyser.GetLatestHOGFeature(), face_analyser.GetHOGRows(), face_analyser.GetHOGCols());
visualizer.SetObservationLandmarks(landmarks, confidence, visibilities);
visualizer.SetObservationPose(pose, confidence);
visualizer.SetObservationGaze(gaze_analyser.GetGazeCamera().Item1, gaze_analyser.GetGazeCamera().Item2, landmark_detector.CalculateAllEyeLandmarks(), landmark_detector.CalculateAllEyeLandmarks3D(fx, fy, cx, cy), confidence);
eye_landmarks = landmark_detector.CalculateVisibleEyeLandmarks();
lines = landmark_detector.CalculateBox(fx, fy, cx, cy);
gaze_lines = gaze_analyser.CalculateGazeLines(fx, fy, cx, cy);
gaze_angle = gaze_analyser.GetGazeAngle();
// Visualisation (as a separate function)
Dispatcher.Invoke(DispatcherPriority.Render, new TimeSpan(0, 0, 0, 0, 200), (Action)(() =>
{
if (ShowAUs)
{
var au_classes = face_analyser.GetCurrentAUsClass();
var au_regs = face_analyser.GetCurrentAUsReg();
auClassGraph.Update(au_classes);
var au_regs_scaled = new Dictionary <String, double>();
foreach (var au_reg in au_regs)
{
au_regs_scaled[au_reg.Key] = au_reg.Value / 5.0;
if (au_regs_scaled[au_reg.Key] < 0)
{
au_regs_scaled[au_reg.Key] = 0;
}
if (au_regs_scaled[au_reg.Key] > 1)
{
au_regs_scaled[au_reg.Key] = 1;
}
}
auRegGraph.Update(au_regs_scaled);
}
if (ShowGeometry)
{
int yaw = (int)(pose[4] * 180 / Math.PI + 0.5);
int roll = (int)(pose[5] * 180 / Math.PI + 0.5);
int pitch = (int)(pose[3] * 180 / Math.PI + 0.5);
YawLabel.Content = yaw + "°";
RollLabel.Content = roll + "°";
PitchLabel.Content = pitch + "°";
XPoseLabel.Content = (int)pose[0] + " mm";
YPoseLabel.Content = (int)pose[1] + " mm";
ZPoseLabel.Content = (int)pose[2] + " mm";
nonRigidGraph.Update(non_rigid_params);
// Update eye gaze
String x_angle = String.Format("{0:F0}°", gaze_angle.Item1 * (180.0 / Math.PI));
String y_angle = String.Format("{0:F0}°", gaze_angle.Item2 * (180.0 / Math.PI));
GazeXLabel.Content = x_angle;
GazeYLabel.Content = y_angle;
}
if (ShowTrackedVideo)
{
if (new_image)
{
latest_img = frame.CreateWriteableBitmap();
overlay_image.Clear();
}
frame.UpdateWriteableBitmap(latest_img);
// Clear results from previous image
overlay_image.Source = latest_img;
overlay_image.Confidence.Add(confidence);
overlay_image.FPS = processing_fps.GetFPS();
overlay_image.Progress = progress;
overlay_image.FaceScale.Add(scale);
// Update results even if it is not succeeding when in multi-face mode
if (detection_succeeding || multi_face)
{
List <Point> landmark_points = new List <Point>();
foreach (var p in landmarks)
{
landmark_points.Add(new Point(p.Item1, p.Item2));
}
List <Point> eye_landmark_points = new List <Point>();
foreach (var p in eye_landmarks)
{
eye_landmark_points.Add(new Point(p.Item1, p.Item2));
}
overlay_image.OverlayLines.Add(lines);
overlay_image.OverlayPoints.Add(landmark_points);
overlay_image.OverlayPointsVisibility.Add(visibilities);
overlay_image.OverlayEyePoints.Add(eye_landmark_points);
overlay_image.GazeLines.Add(gaze_lines);
}
}
if (ShowAppearance)
{
RawImage aligned_face = face_analyser.GetLatestAlignedFace();
RawImage hog_face = visualizer.GetHOGVis();
if (latest_aligned_face == null)
{
latest_aligned_face = aligned_face.CreateWriteableBitmap();
latest_HOG_descriptor = hog_face.CreateWriteableBitmap();
}
aligned_face.UpdateWriteableBitmap(latest_aligned_face);
hog_face.UpdateWriteableBitmap(latest_HOG_descriptor);
AlignedFace.Source = latest_aligned_face;
AlignedHOG.Source = latest_HOG_descriptor;
}
}));
}
// Capturing and processing the video frame by frame
private void VideoLoop(UtilitiesOF.SequenceReader reader)
{
Thread.CurrentThread.IsBackground = true;
String root = AppDomain.CurrentDomain.BaseDirectory;
FaceModelParameters model_params = new FaceModelParameters(root, true, false, false);
// Initialize the face detector
FaceDetector face_detector = new FaceDetector(model_params.GetHaarLocation(), model_params.GetMTCNNLocation());
// If MTCNN model not available, use HOG
if (!face_detector.IsMTCNNLoaded())
{
model_params.SetFaceDetector(false, true, false);
}
CLNF face_model = new CLNF(model_params);
GazeAnalyserManaged gaze_analyser = new GazeAnalyserManaged();
DateTime?startTime = CurrentTime;
var lastFrameTime = CurrentTime;
while (running)
{
//////////////////////////////////////////////
// CAPTURE FRAME AND DETECT LANDMARKS FOLLOWED BY THE REQUIRED IMAGE PROCESSING
//////////////////////////////////////////////
RawImage frame = reader.GetNextImage();
lastFrameTime = CurrentTime;
processing_fps.AddFrame();
var grayFrame = reader.GetCurrentFrameGray();
if (mirror_image)
{
frame.Mirror();
grayFrame.Mirror();
}
bool detectionSucceeding = ProcessFrame(face_model, gaze_analyser, model_params, frame, grayFrame, reader.GetFx(), reader.GetFy(), reader.GetCx(), reader.GetCy());
lock (recording_lock)
{
if (recording)
{
// Add objects to recording queues
List <float> pose = new List <float>();
face_model.GetPose(pose, reader.GetFx(), reader.GetFy(), reader.GetCx(), reader.GetCy());
RawImage image = new RawImage(frame);
recording_objects.Enqueue(new Tuple <RawImage, bool, List <float> >(image, detectionSucceeding, pose));
}
}
List <Tuple <System.Windows.Point, System.Windows.Point> > lines = null;
List <Tuple <float, float> > eye_landmarks = null;
List <System.Windows.Point> landmarks = new List <System.Windows.Point>();
List <Tuple <System.Windows.Point, System.Windows.Point> > gaze_lines = null;
Tuple <float, float> gaze_angle = new Tuple <float, float>(0, 0);
var visibilities = face_model.GetVisibilities();
double scale = face_model.GetRigidParams()[0];
if (detectionSucceeding)
{
List <Tuple <float, float> > landmarks_doubles = face_model.CalculateAllLandmarks();
foreach (var p in landmarks_doubles)
{
landmarks.Add(new System.Windows.Point(p.Item1, p.Item2));
}
eye_landmarks = face_model.CalculateVisibleEyeLandmarks();
gaze_lines = gaze_analyser.CalculateGazeLines(reader.GetFx(), reader.GetFy(), reader.GetCx(), reader.GetCy());
gaze_angle = gaze_analyser.GetGazeAngle();
lines = face_model.CalculateBox(reader.GetFx(), reader.GetFy(), reader.GetCx(), reader.GetCy());
}
if (reset)
{
face_model.Reset();
reset = false;
}
// Visualisation updating
try
{
Dispatcher.Invoke(DispatcherPriority.Render, new TimeSpan(0, 0, 0, 0, 200), (Action)(() =>
{
if (latest_img == null)
{
latest_img = frame.CreateWriteableBitmap();
}
List <float> pose = new List <float>();
face_model.GetPose(pose, reader.GetFx(), reader.GetFy(), reader.GetCx(), reader.GetCy());
int yaw = (int)(pose[4] * 180 / Math.PI + 0.5);
int yaw_abs = Math.Abs(yaw);
int roll = (int)(pose[5] * 180 / Math.PI + 0.5);
int roll_abs = Math.Abs(roll);
int pitch = (int)(pose[3] * 180 / Math.PI + 0.5);
int pitch_abs = Math.Abs(pitch);
YawLabel.Content = yaw_abs + "°";
RollLabel.Content = roll_abs + "°";
PitchLabel.Content = pitch_abs + "°";
if (yaw > 0)
{
YawLabelDir.Content = "Right";
}
else if (yaw < 0)
{
YawLabelDir.Content = "Left";
}
else
{
YawLabelDir.Content = "Straight";
}
if (pitch > 0)
{
PitchLabelDir.Content = "Down";
}
else if (pitch < 0)
{
PitchLabelDir.Content = "Up";
}
else
{
PitchLabelDir.Content = "Straight";
}
if (roll > 0)
{
RollLabelDir.Content = "Left";
}
else if (roll < 0)
{
RollLabelDir.Content = "Right";
}
else
{
RollLabelDir.Content = "Straight";
}
XPoseLabel.Content = (int)pose[0] + " mm";
YPoseLabel.Content = (int)pose[1] + " mm";
ZPoseLabel.Content = (int)pose[2] + " mm";
String x_angle = String.Format("{0:F0}°", gaze_angle.Item1 * (180.0 / Math.PI));
String y_angle = String.Format("{0:F0}°", gaze_angle.Item2 * (180.0 / Math.PI));
YawLabelGaze.Content = x_angle;
PitchLabelGaze.Content = y_angle;
if (gaze_angle.Item1 > 0)
{
YawLabelGazeDir.Content = "Right";
}
else if (gaze_angle.Item1 < 0)
{
YawLabelGazeDir.Content = "Left";
}
else
{
YawLabelGazeDir.Content = "Straight";
}
if (gaze_angle.Item2 > 0)
{
PitchLabelGazeDir.Content = "Down";
}
else if (gaze_angle.Item2 < 0)
{
PitchLabelGazeDir.Content = "Up";
}
else
{
PitchLabelGazeDir.Content = "Straight";
}
double confidence = face_model.GetConfidence();
if (confidence < 0)
{
confidence = 0;
}
else if (confidence > 1)
{
confidence = 1;
}
frame.UpdateWriteableBitmap(latest_img);
webcam_img.Clear();
webcam_img.Source = latest_img;
webcam_img.Confidence.Add(confidence);
webcam_img.FPS = processing_fps.GetFPS();
if (detectionSucceeding)
{
webcam_img.OverlayLines.Add(lines);
webcam_img.OverlayPoints.Add(landmarks);
webcam_img.OverlayPointsVisibility.Add(visibilities);
webcam_img.FaceScale.Add(scale);
List <System.Windows.Point> eye_landmark_points = new List <System.Windows.Point>();
foreach (var p in eye_landmarks)
{
eye_landmark_points.Add(new System.Windows.Point(p.Item1, p.Item2));
}
webcam_img.OverlayEyePoints.Add(eye_landmark_points);
webcam_img.GazeLines.Add(gaze_lines);
// Publish the information for other applications
String str_head_pose = String.Format("{0}:{1:F2}, {2:F2}, {3:F2}, {4:F2}, {5:F2}, {6:F2}", "HeadPose", pose[0], pose[1], pose[2],
pose[3] * 180 / Math.PI, pose[4] * 180 / Math.PI, pose[5] * 180 / Math.PI);
zero_mq_socket.Send(new ZFrame(str_head_pose, Encoding.UTF8));
String str_gaze = String.Format("{0}:{1:F2}, {2:F2}", "GazeAngle", gaze_angle.Item1 * (180.0 / Math.PI), gaze_angle.Item2 * (180.0 / Math.PI));
zero_mq_socket.Send(new ZFrame(str_gaze, Encoding.UTF8));
}
}));
while (running & pause)
{
Thread.Sleep(10);
}
}
catch (TaskCanceledException)
{
// Quitting
break;
}
}
reader.Close();
System.Console.Out.WriteLine("Thread finished");
}