// 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;
}
// Capturing and processing the video frame by frame
/* private void RecordingLoop()
* {
* // Set up the recording objects first
* Thread.CurrentThread.IsBackground = true;
*
* System.IO.StreamWriter output_head_pose_file = null;
*
* if (record_head_pose)
* {
* String filename_poses = output_root + "/trial_" + trial_id + ".poses.txt";
* output_head_pose_file = new System.IO.StreamWriter(filename_poses);
* output_head_pose_file.WriteLine("time(ms), success, pose_X(mm), pose_Y(mm), pose_Z(mm), pitch(deg), yaw(deg), roll(deg)");
* }
*
* VideoWriter video_writer = null;
*
* if (record_video)
* {
* double fps = processing_fps.GetFPS();
* String filename_video = output_root + "/trial_" + trial_id + ".avi";
* video_writer = new VideoWriter(filename_video, img_width, img_height, fps, true);
* }
*
* // The timiing should be when the item is captured, but oh well
* Stopwatch stopWatch = new Stopwatch();
* stopWatch.Start();
*
* while (recording)
* {
* Tuple<RawImage, bool, List<double>> recording_object;
* if (recording_objects.TryDequeue(out recording_object))
* {
*
* if (record_video)
* {
* video_writer.Write(recording_object.Item1);
* }
*
* if (record_head_pose)
* {
* String output_pose_line = stopWatch.ElapsedMilliseconds.ToString();
* if (recording_object.Item2)
* output_pose_line += ", 1";
* else
* output_pose_line += ", 0";
*
* for (int i = 0; i < recording_object.Item3.Count; ++i)
* {
* double num = recording_object.Item3[i];
* if (i > 2)
* {
* output_pose_line += ", " + num * 180 / Math.PI;
* }
* else
* {
* output_pose_line += ", " + num;
* }
* }
* output_head_pose_file.WriteLine(output_pose_line);
* }
* }
*
* Thread.Sleep(10);
* }
*
* // Clean up the recording
* if (record_head_pose)
* {
* output_head_pose_file.Close();
* }
* }
*
* // 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, 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 <double> pose = new List <double>();
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 <double> >(image, detectionSucceeding, pose));
}
}
List <Tuple <System.Windows.Point, System.Windows.Point> > lines = null;
List <Tuple <double, double> > 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 <double, double> gaze_angle = new Tuple <double, double>(0, 0);
double scale = face_model.GetRigidParams()[0];
if (detectionSucceeding)
{
List <Tuple <double, double> > landmarks_doubles = face_model.CalculateVisibleLandmarks();
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 <double> pose = new List <double>();
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 + "°";
var message = new SharpOSC.OscMessage("/n_set", 1006, "freq", (pitch_abs * 10) + 150);
var oscSender = new SharpOSC.UDPSender("127.0.0.1", 57110);
oscSender.Send(message);
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.Source = latest_img;
webcam_img.Confidence = confidence;
webcam_img.FPS = processing_fps.GetFPS();
if (!detectionSucceeding)
{
webcam_img.OverlayLines.Clear();
webcam_img.OverlayPoints.Clear();
webcam_img.OverlayEyePoints.Clear();
webcam_img.GazeLines.Clear();
}
else
{
webcam_img.OverlayLines = lines;
webcam_img.OverlayPoints = landmarks;
webcam_img.FaceScale = 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 = eye_landmark_points;
webcam_img.GazeLines = 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");
}