sustaining_gazes/lib/local/LandmarkDetector/include/SVR_patch_expert.h
2016-04-28 15:40:36 -04:00

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///////////////////////////////////////////////////////////////////////////////
// Copyright (C) 2016, Carnegie Mellon University and University of Cambridge,
// all rights reserved.
//
// THIS SOFTWARE IS PROVIDED “AS IS” FOR ACADEMIC USE ONLY AND ANY EXPRESS
// OR IMPLIED WARRANTIES WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
// THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
// HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
// STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
// ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
//
// 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
// Licensees 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
// License Agreement with respect to such Open Source Component, such restrictions will not
// 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
// 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
// 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 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 __SVR_PATCH_EXPERT_h_
#define __SVR_PATCH_EXPERT_h_
// system includes
#include <map>
// OpenCV includes
#include <opencv2/core/core.hpp>
namespace LandmarkDetector
{
//===========================================================================
/**
The classes describing the SVR patch experts
*/
class SVR_patch_expert{
public:
// Type of data the patch expert operated on (0=raw, 1=grad)
int type;
// Logistic regression slope
double scaling;
// Logistic regression bias
double bias;
// Support vector regression weights
cv::Mat_<float> weights;
// Discrete Fourier Transform of SVR weights, precalculated for speed (at different window sizes)
std::map<int, cv::Mat_<double> > weights_dfts;
// Confidence of the current patch expert (used for NU_RLMS optimisation)
double confidence;
SVR_patch_expert(){;}
// A copy constructor
SVR_patch_expert(const SVR_patch_expert& other);
// Reading in the patch expert
void Read(std::ifstream &stream);
// The actual response computation from intensity or depth (for CLM-Z)
void Response(const cv::Mat_<float> &area_of_interest, cv::Mat_<float> &response);
void ResponseDepth(const cv::Mat_<float> &area_of_interest, cv::Mat_<float> &response);
};
//===========================================================================
/**
A Multi-patch Expert that can include different patch types. Raw pixel values or image gradients
*/
class Multi_SVR_patch_expert{
public:
// Width and height of the patch expert support area
int width;
int height;
// Vector of all of the patch experts (different modalities) for this particular Multi patch expert
std::vector<SVR_patch_expert> svr_patch_experts;
// Default constructor
Multi_SVR_patch_expert(){;}
// Copy constructor
Multi_SVR_patch_expert(const Multi_SVR_patch_expert& other);
void Read(std::ifstream &stream);
// actual response computation from intensity of depth (for CLM-Z)
void Response(const cv::Mat_<float> &area_of_interest, cv::Mat_<float> &response);
void ResponseDepth(const cv::Mat_<float> &area_of_interest, cv::Mat_<float> &response);
};
}
#endif