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///////////////////////////////////////////////////////////////////////////////
// Copyright (C) 2016, Carnegie Mellon University and University of Cambridge,
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// provide a list of Open Source Components for a particular version of the Software upon
// Licensee<65> 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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// apply to such Open Source Component. To the extent the terms of the licenses applicable to
// Open Source Components require Licensor to make an offer to provide source code or
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// 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
// delivery of the Software.
// * 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 SVR patch experts (for depth/range images), the experts are laid out scale->view->landmark
vector < vector < vector < Multi_SVR_patch_expert > > > svr_expert_depth ;
// 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 and an optional depth image.
// 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 , const cv : : Mat_ < float > & depth_image ,
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 > depth_svr_expert_locations , vector < string > intensity_ccnf_expert_locations ) ;
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
