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// Copyright (C) 2016, Carnegie Mellon University and University of Cambridge,
// all rights reserved.
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// Notwithstanding the license granted herein, Licensee acknowledges that certain components
// of the Software may be covered by so-called “open source” software licenses (“Open Source
// Components”), which means any software licenses approved as open source licenses by the
// Open Source Initiative or any substantially similar licenses, including without limitation any
// license that, as a condition of distribution of the software licensed under such license,
// requires that the distributor make the software available in source code format. Licensor shall
// provide a list of Open Source Components for a particular version of the Software upon
// Licensee’s request. Licensee will comply with the applicable terms of such licenses and to
// the extent required by the licenses covering Open Source Components, the terms of such
// licenses will apply in lieu of the terms of this Agreement. To the extent the terms of the
// licenses applicable to Open Source Components prohibit any of the restrictions in this
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// Open Source Components require Licensor to make an offer to provide source code or
// related information in connection with the Software, such offer is hereby made. Any request
// for source code or related information should be directed to cl-face-tracker-distribution@lists.cam.ac.uk
// Licensee acknowledges receipt of notices for the Open Source Components for the initial
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//     * 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.    
//
///////////////////////////////////////////////////////////////////////////////

#ifndef __FACE_UTILS_h_
#define __FACE_UTILS_h_

#include <LandmarkCoreIncludes.h>

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>

namespace FaceAnalysis
{
	//===========================================================================	
	// Defining a set of useful utility functions to be used within FaceAnalyser

	// Aligning a face to a common reference frame
	void AlignFace(cv::Mat& aligned_face, const cv::Mat& frame, const LandmarkDetector::CLNF& clnf_model, bool rigid = true, double scale = 0.6, int width = 96, int height = 96);
	void AlignFaceMask(cv::Mat& aligned_face, const cv::Mat& frame, const LandmarkDetector::CLNF& clnf_model, const cv::Mat_<int>& triangulation, bool rigid = true, double scale = 0.6, int width = 96, int height = 96);

	void Extract_FHOG_descriptor(cv::Mat_<double>& descriptor, const cv::Mat& image, int& num_rows, int& num_cols, int cell_size = 8);

	void Visualise_FHOG(const cv::Mat_<double>& descriptor, int num_rows, int num_cols, cv::Mat& visualisation);

	// The following two methods go hand in hand
	void ExtractSummaryStatistics(const cv::Mat_<double>& descriptors, cv::Mat_<double>& sum_stats, bool mean, bool stdev, bool max_min);
	void AddDescriptor(cv::Mat_<double>& descriptors, cv::Mat_<double> new_descriptor, int curr_frame, int num_frames_to_keep = 120);

}
#endif