143 lines
6.1 KiB
C
143 lines
6.1 KiB
C
|
///////////////////////////////////////////////////////////////////////////////
|
|||
|
// Copyright (C) 2016, Carnegie Mellon University and University of Cambridge,
|
|||
|
// all rights reserved.
|
|||
|
//
|
|||
|
// THIS SOFTWARE IS PROVIDED <20>AS IS<49> 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
|
|||
|
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS
|
|||
|
// BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY.
|
|||
|
// OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
|
|||
|
// 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 <20>open source<63> software licenses (<28>Open Source
|
|||
|
// Components<74>), 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<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
|
|||
|
// 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 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.
|
|||
|
//
|
|||
|
///////////////////////////////////////////////////////////////////////////////
|
|||
|
|
|||
|
// Parameters of the CLNF, CLM-Z and CLM trackers
|
|||
|
#ifndef __LANDMARK_DETECTOR_PARAM_H
|
|||
|
#define __LANDMARK_DETECTOR_PARAM_H
|
|||
|
|
|||
|
#include <vector>
|
|||
|
|
|||
|
using namespace std;
|
|||
|
|
|||
|
namespace LandmarkDetector
|
|||
|
{
|
|||
|
|
|||
|
struct FaceModelParameters
|
|||
|
{
|
|||
|
|
|||
|
// A number of RLMS or NU-RLMS iterations
|
|||
|
int num_optimisation_iteration;
|
|||
|
|
|||
|
// Should pose be limited to 180 degrees frontal
|
|||
|
bool limit_pose;
|
|||
|
|
|||
|
// Should face validation be done
|
|||
|
bool validate_detections;
|
|||
|
|
|||
|
// Landmark detection validator boundary for correct detection, the regressor output -1 (perfect alignment) 1 (bad alignment),
|
|||
|
double validation_boundary;
|
|||
|
|
|||
|
// Used when tracking is going well
|
|||
|
vector<int> window_sizes_small;
|
|||
|
|
|||
|
// Used when initialising or tracking fails
|
|||
|
vector<int> window_sizes_init;
|
|||
|
|
|||
|
// Used for the current frame
|
|||
|
vector<int> window_sizes_current;
|
|||
|
|
|||
|
// How big is the tracking template that helps with large motions
|
|||
|
double face_template_scale;
|
|||
|
bool use_face_template;
|
|||
|
|
|||
|
// Where to load the model from
|
|||
|
string model_location;
|
|||
|
|
|||
|
// this is used for the smooting of response maps (KDE sigma)
|
|||
|
double sigma;
|
|||
|
|
|||
|
double reg_factor; // weight put to regularisation
|
|||
|
double weight_factor; // factor for weighted least squares
|
|||
|
|
|||
|
// should multiple views be considered during reinit
|
|||
|
bool multi_view;
|
|||
|
|
|||
|
// How often should face detection be used to attempt reinitialisation, every n frames (set to negative not to reinit)
|
|||
|
int reinit_video_every;
|
|||
|
|
|||
|
// Determining which face detector to use for (re)initialisation, HAAR is quicker but provides more false positives and is not goot for in-the-wild conditions
|
|||
|
// Also HAAR detector can detect smaller faces while HOG SVM is only capable of detecting faces at least 70px across
|
|||
|
enum FaceDetector{HAAR_DETECTOR, HOG_SVM_DETECTOR};
|
|||
|
|
|||
|
string face_detector_location;
|
|||
|
FaceDetector curr_face_detector;
|
|||
|
|
|||
|
// Should the results be visualised and reported to console
|
|||
|
bool quiet_mode;
|
|||
|
|
|||
|
// Should the model be refined hierarchically (if available)
|
|||
|
bool refine_hierarchical;
|
|||
|
|
|||
|
// Should the parameters be refined for different scales
|
|||
|
bool refine_parameters;
|
|||
|
|
|||
|
// Using the brand new and experimental gaze tracker
|
|||
|
bool track_gaze;
|
|||
|
|
|||
|
FaceModelParameters();
|
|||
|
|
|||
|
FaceModelParameters(vector<string> &arguments);
|
|||
|
|
|||
|
private:
|
|||
|
void init();
|
|||
|
};
|
|||
|
|
|||
|
}
|
|||
|
|
|||
|
#endif // __LANDMARK_DETECTOR_PARAM_H
|