sustaining_gazes/lib/local/LandmarkDetector/include/Patch_experts.h

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///////////////////////////////////////////////////////////////////////////////
// Copyright (C) 2017, Carnegie Mellon University and University of Cambridge,
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// 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
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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 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.
//
///////////////////////////////////////////////////////////////////////////////
#ifndef __Patch_experts_h_
#define __Patch_experts_h_
// OpenCV includes
#include <opencv2/core/core.hpp>
#include "SVR_patch_expert.h"
#include "CCNF_patch_expert.h"
#include "PDM.h"
namespace LandmarkDetector
{
//===========================================================================
/**
Combined class for all of the patch experts
*/
class Patch_experts
{
public:
// The collection of SVR patch experts (for intensity/grayscale images), the experts are laid out scale->view->landmark
vector<vector<vector<Multi_SVR_patch_expert> > > svr_expert_intensity;
// The collection of LNF (CCNF) patch experts (for intensity images), the experts are laid out scale->view->landmark
vector<vector<vector<CCNF_patch_expert> > > ccnf_expert_intensity;
// The node connectivity for CCNF experts, at different window sizes and corresponding to separate edge features
vector<vector<cv::Mat_<float> > > sigma_components;
// The available scales for intensity patch experts
vector<double> patch_scaling;
// The available views for the patch experts at every scale (in radians)
vector<vector<cv::Vec3d> > centers;
// Landmark visibilities for each scale and view
vector<vector<cv::Mat_<int> > > visibilities;
// A default constructor
Patch_experts(){;}
// A copy constructor
Patch_experts(const Patch_experts& other);
// Returns the patch expert responses given a grayscale image.
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// Additionally returns the transform from the image coordinates to the response coordinates (and vice versa).
// The computation also requires the current landmark locations to compute response around, the PDM corresponding to the desired model, and the parameters describing its instance
// Also need to provide the size of the area of interest and the desired scale of analysis
void Response(vector<cv::Mat_<float> >& patch_expert_responses, cv::Matx22f& sim_ref_to_img, cv::Matx22d& sim_img_to_ref, const cv::Mat_<uchar>& grayscale_image,
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const PDM& pdm, const cv::Vec6d& params_global, const cv::Mat_<double>& params_local, int window_size, int scale);
// Getting the best view associated with the current orientation
int GetViewIdx(const cv::Vec6d& params_global, int scale) const;
// The number of views at a particular scale
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inline int nViews(size_t scale = 0) const { return (int)centers[scale].size(); };
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// Reading in all of the patch experts
void Read(vector<string> intensity_svr_expert_locations, vector<string> intensity_ccnf_expert_locations);
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private:
void Read_SVR_patch_experts(string expert_location, std::vector<cv::Vec3d>& centers, std::vector<cv::Mat_<int> >& visibility, std::vector<std::vector<Multi_SVR_patch_expert> >& patches, double& scale);
void Read_CCNF_patch_experts(string patchesFileLocation, std::vector<cv::Vec3d>& centers, std::vector<cv::Mat_<int> >& visibility, std::vector<std::vector<CCNF_patch_expert> >& patches, double& patchScaling);
};
}
#endif