sustaining_gazes/exe/FaceLandmarkVid/FaceLandmarkVid.cpp

191 lines
6.6 KiB
C++
Raw Normal View History

2016-04-28 19:40:36 +00:00
///////////////////////////////////////////////////////////////////////////////
// Copyright (C) 2017, Carnegie Mellon University and University of Cambridge,
2016-04-28 19:40:36 +00:00
// all rights reserved.
//
// ACADEMIC OR NON-PROFIT ORGANIZATION NONCOMMERCIAL RESEARCH USE ONLY
2016-04-28 19:40:36 +00:00
//
// 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
2016-04-28 19:40:36 +00:00
// * 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 Baltru<72>aitis, 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 Baltru<72>aitis, 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 Baltru<72>aitis, 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 Baltru<72>aitis, Peter Robinson, and Louis-Philippe Morency.
// in IEEE Int. Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge, 2013.
//
///////////////////////////////////////////////////////////////////////////////
// FaceTrackingVid.cpp : Defines the entry point for the console application for tracking faces in videos.
// Libraries for landmark detection (includes CLNF and CLM modules)
#include "LandmarkCoreIncludes.h"
#include "GazeEstimation.h"
#include <fstream>
#include <sstream>
// OpenCV includes
#include <opencv2/videoio/videoio.hpp> // Video write
#include <opencv2/videoio/videoio_c.h> // Video write
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <SequenceCapture.h>
#include <Visualizer.h>
#include <VisualizationUtils.h>
2016-04-28 19:40:36 +00:00
// Boost includes
#include <filesystem.hpp>
#include <filesystem/fstream.hpp>
#define INFO_STREAM( stream ) \
std::cout << stream << std::endl
#define WARN_STREAM( stream ) \
std::cout << "Warning: " << stream << std::endl
#define ERROR_STREAM( stream ) \
std::cout << "Error: " << stream << std::endl
static void printErrorAndAbort( const std::string & error )
{
std::cout << error << std::endl;
abort();
}
#define FATAL_STREAM( stream ) \
printErrorAndAbort( std::string( "Fatal error: " ) + stream )
using namespace std;
vector<string> get_arguments(int argc, char **argv)
{
vector<string> arguments;
for(int i = 0; i < argc; ++i)
{
arguments.push_back(string(argv[i]));
}
return arguments;
}
int main (int argc, char **argv)
{
vector<string> arguments = get_arguments(argc, argv);
LandmarkDetector::FaceModelParameters det_parameters(arguments);
// The modules that are being used for tracking
LandmarkDetector::CLNF face_model(det_parameters.model_location);
2016-04-28 19:40:36 +00:00
// Open a sequence
Utilities::SequenceCapture sequence_reader;
2016-04-28 19:40:36 +00:00
// A utility for visualizing the results (show just the tracks)
Utilities::Visualizer visualizer(true, false, false);
// Tracking FPS for visualization
Utilities::FpsTracker fps_tracker;
fps_tracker.AddFrame();
while (true) // this is not a for loop as we might also be reading from a webcam
2016-04-28 19:40:36 +00:00
{
// The sequence reader chooses what to open based on command line arguments provided
if(!sequence_reader.Open(arguments) && sequence_reader.no_input_specified)
2016-04-28 19:40:36 +00:00
{
// If that fails, revert to webcam
INFO_STREAM("No input specified, attempting to open a webcam 0");
if (!sequence_reader.OpenWebcam(0))
ERROR_STREAM("Failed to open the webcam");
2016-04-28 19:40:36 +00:00
}
else
{
ERROR_STREAM("Failed to open a sequence");
break;
2016-04-28 19:40:36 +00:00
}
INFO_STREAM("Device or file opened");
2016-04-28 19:40:36 +00:00
cv::Mat captured_image = sequence_reader.GetNextFrame();
2016-04-28 19:40:36 +00:00
INFO_STREAM("Starting tracking");
while (!captured_image.empty()) // this is not a for loop as we might also be reading from a webcam
2016-04-28 19:40:36 +00:00
{
// Reading the images
cv::Mat_<uchar> grayscale_image = sequence_reader.GetGrayFrame();
2016-04-28 19:40:36 +00:00
// The actual facial landmark detection / tracking
bool detection_success = LandmarkDetector::DetectLandmarksInVideo(grayscale_image, face_model, det_parameters);
2016-04-28 19:40:36 +00:00
// Gaze tracking, absolute gaze direction
cv::Point3f gazeDirection0(0, 0, -1);
cv::Point3f gazeDirection1(0, 0, -1);
// If tracking succeeded and we have an eye model, estimate gaze
if (detection_success && face_model.eye_model)
2016-04-28 19:40:36 +00:00
{
GazeAnalysis::EstimateGaze(face_model, gazeDirection0, sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy, true);
GazeAnalysis::EstimateGaze(face_model, gazeDirection1, sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy, false);
2016-04-28 19:40:36 +00:00
}
// Work out the pose of the head from the tracked model
cv::Vec6d pose_estimate = LandmarkDetector::GetPose(face_model, sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy);
// Keeping track of FPS
fps_tracker.AddFrame();
// Displaying the tracking visualizations
visualizer.SetImage(captured_image, sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy);
visualizer.SetObservationLandmarks(face_model.detected_landmarks, face_model.detection_certainty, detection_success);
visualizer.SetObservationPose(pose_estimate, face_model.detection_certainty);
visualizer.SetObservationGaze(gazeDirection0, gazeDirection1, LandmarkDetector::CalculateAllEyeLandmarks(face_model), LandmarkDetector::Calculate3DEyeLandmarks(face_model, sequence_reader.fx, sequence_reader.fy, sequence_reader.cx, sequence_reader.cy), face_model.detection_certainty);
visualizer.SetFps(fps_tracker.GetFPS());
visualizer.ShowObservation();
2016-04-28 19:40:36 +00:00
// detect key presses
char character_press = cv::waitKey(1);
2016-04-28 19:40:36 +00:00
// restart the tracker
if (character_press == 'r')
2016-04-28 19:40:36 +00:00
{
face_model.Reset();
2016-04-28 19:40:36 +00:00
}
// quit the application
else if (character_press == 'q')
2016-04-28 19:40:36 +00:00
{
return(0);
}
// Grabbing the next frame in the sequence
captured_image = sequence_reader.GetNextFrame();
2016-04-28 19:40:36 +00:00
}
// Reset the model, for the next video
face_model.Reset();
2016-04-28 19:40:36 +00:00
}
2016-04-28 19:40:36 +00:00
return 0;
}