///////////////////////////////////////////////////////////////////////////////
// Copyright (C) 2017, Carnegie Mellon University and University of Cambridge,
// all rights reserved.
//
// ACADEMIC OR NON-PROFIT ORGANIZATION NONCOMMERCIAL RESEARCH USE ONLY
//
// BY USING OR DOWNLOADING THE SOFTWARE, YOU ARE AGREEING TO THE TERMS OF THIS LICENSE AGREEMENT.
// IF YOU DO NOT AGREE WITH THESE TERMS, YOU MAY NOT USE OR DOWNLOAD THE SOFTWARE.
//
// License can be found in OpenFace-license.txt
// * Any publications arising from the use of this software, including but
// not limited to academic journal and conference publications, technical
// reports and manuals, must cite at least one of the following works:
//
// OpenFace: an open source facial behavior analysis toolkit
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency
// in IEEE Winter Conference on Applications of Computer Vision, 2016
//
// Rendering of Eyes for Eye-Shape Registration and Gaze Estimation
// Erroll Wood, Tadas Baltrušaitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling
// in IEEE International. Conference on Computer Vision (ICCV), 2015
//
// Cross-dataset learning and person-speci?c normalisation for automatic Action Unit detection
// Tadas Baltrušaitis, Marwa Mahmoud, and Peter Robinson
// in Facial Expression Recognition and Analysis Challenge,
// IEEE International Conference on Automatic Face and Gesture Recognition, 2015
//
// Constrained Local Neural Fields for robust facial landmark detection in the wild.
// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency.
// in IEEE Int. Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge, 2013.
//
///////////////////////////////////////////////////////////////////////////////
using System;
using System.Collections.Generic;
using System.Windows;
using System.Windows.Controls;
using System.Windows.Data;
using System.Windows.Documents;
using System.Windows.Input;
using System.Windows.Media;
using System.Windows.Media.Imaging;
using System.Threading;
using System.Windows.Threading;
using System.Diagnostics;
// Internal libraries
using OpenFaceOffline;
using OpenCVWrappers;
using CppInterop.LandmarkDetector;
using FaceAnalyser_Interop;
using GazeAnalyser_Interop;
using UtilitiesOF;
namespace OpenFaceDemo
{
///
/// Interaction logic for MainWindow.xaml
///
public partial class MainWindow : Window
{
// -----------------------------------------------------------------
// Members
// -----------------------------------------------------------------
// Timing for measuring FPS
#region High-Resolution Timing
static DateTime startTime;
static Stopwatch sw = new Stopwatch();
static MainWindow()
{
startTime = DateTime.Now;
sw.Start();
}
public static DateTime CurrentTime
{
get { return startTime + sw.Elapsed; }
}
#endregion
Thread processing_thread;
// Some members for displaying the results
private WriteableBitmap latest_img;
private volatile bool thread_running;
FpsTracker processing_fps = new FpsTracker();
// Controlling the model reset
volatile bool reset = false;
Point? resetPoint = null;
// For selecting webcams
CameraSelection cam_sec;
// For tracking
FaceModelParameters face_model_params;
CLNF landmark_detector;
FaceAnalyserManaged face_analyser;
GazeAnalyserManaged gaze_analyser;
public MainWindow()
{
InitializeComponent();
// Set the icon
Uri iconUri = new Uri("logo1.ico", UriKind.RelativeOrAbsolute);
this.Icon = BitmapFrame.Create(iconUri);
String root = AppDomain.CurrentDomain.BaseDirectory;
// TODO, create a demo version of parameters
face_model_params = new FaceModelParameters(root, false);
landmark_detector = new CLNF(face_model_params);
face_analyser = new FaceAnalyserManaged(root, true, 112, true);
gaze_analyser = new GazeAnalyserManaged();
Dispatcher.Invoke(DispatcherPriority.Render, new TimeSpan(0, 0, 0, 0, 200), (Action)(() =>
{
headPosePlot.AssocColor(0, Colors.Blue);
headPosePlot.AssocColor(1, Colors.Red);
headPosePlot.AssocColor(2, Colors.Green);
headPosePlot.AssocName(1, "Turn");
headPosePlot.AssocName(2, "Tilt");
headPosePlot.AssocName(0, "Up/Down");
headPosePlot.AssocThickness(0, 2);
headPosePlot.AssocThickness(1, 2);
headPosePlot.AssocThickness(2, 2);
gazePlot.AssocColor(0, Colors.Red);
gazePlot.AssocColor(1, Colors.Blue);
gazePlot.AssocName(0, "Left-right");
gazePlot.AssocName(1, "Up-down");
gazePlot.AssocThickness(0, 2);
gazePlot.AssocThickness(1, 2);
smilePlot.AssocColor(0, Colors.Green);
smilePlot.AssocColor(1, Colors.Red);
smilePlot.AssocName(0, "Smile");
smilePlot.AssocName(1, "Frown");
smilePlot.AssocThickness(0, 2);
smilePlot.AssocThickness(1, 2);
browPlot.AssocColor(0, Colors.Green);
browPlot.AssocColor(1, Colors.Red);
browPlot.AssocName(0, "Raise");
browPlot.AssocName(1, "Furrow");
browPlot.AssocThickness(0, 2);
browPlot.AssocThickness(1, 2);
eyePlot.AssocColor(0, Colors.Green);
eyePlot.AssocColor(1, Colors.Red);
eyePlot.AssocName(0, "Eye widen");
eyePlot.AssocName(1, "Nose wrinkle");
eyePlot.AssocThickness(0, 2);
eyePlot.AssocThickness(1, 2);
}));
}
private void StopTracking()
{
// First complete the running of the thread
if (processing_thread != null)
{
// Tell the other thread to finish
thread_running = false;
processing_thread.Join();
}
}
// 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 pose = new List();
landmark_detector.GetPose(pose, reader.GetFx(), reader.GetFy(), reader.GetCx(), reader.GetCy());
List non_rigid_params = landmark_detector.GetNonRigidParams();
double scale = landmark_detector.GetRigidParams()[0];
double time_stamp = (DateTime.Now - (DateTime)startTime).TotalMilliseconds;
List> lines = null;
List> landmarks = null;
List> eye_landmarks = null;
List> gaze_lines = null;
Tuple 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();
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 smileDict = new Dictionary();
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 browDict = new Dictionary();
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 eyeDict = new Dictionary();
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];
Dictionary poseDict = new Dictionary();
poseDict[0] = -pose[3];
poseDict[1] = pose[4];
poseDict[2] = pose[5];
headPosePlot.AddDataPoint(new DataPointGraph() { Time = CurrentTime, values = poseDict, Confidence = confidence });
Dictionary gazeDict = new Dictionary();
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 landmark_points = new List();
foreach (var p in landmarks)
{
landmark_points.Add(new Point(p.Item1, p.Item2));
}
List eye_landmark_points = new List();
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;
}
// --------------------------------------------------------
// Button handling
// --------------------------------------------------------
private void openWebcamClick(object sender, RoutedEventArgs e)
{
StopTracking();
if (cam_sec == null)
{
cam_sec = new CameraSelection();
}
else
{
cam_sec = new CameraSelection(cam_sec.cams);
cam_sec.Visibility = System.Windows.Visibility.Visible;
}
// Set the icon
Uri iconUri = new Uri("logo1.ico", UriKind.RelativeOrAbsolute);
cam_sec.Icon = BitmapFrame.Create(iconUri);
if (!cam_sec.no_cameras_found)
cam_sec.ShowDialog();
if (cam_sec.camera_selected)
{
int cam_id = cam_sec.selected_camera.Item1;
int width = cam_sec.selected_camera.Item2;
int height = cam_sec.selected_camera.Item3;
SequenceReader reader = new SequenceReader(cam_id, width, height);
processing_thread = new Thread(() => ProcessingLoop(reader));
processing_thread.Name = "Webcam processing";
processing_thread.Start();
}
}
// Cleanup stuff when closing the window
private void Window_Closing(object sender, System.ComponentModel.CancelEventArgs e)
{
if (processing_thread != null)
{
// Stop capture and tracking
thread_running = false;
processing_thread.Join();
}
if (face_analyser != null)
face_analyser.Dispose();
if(landmark_detector != null)
landmark_detector.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;
}
}
}