119 lines
4.1 KiB
C++
119 lines
4.1 KiB
C++
///////////////////////////////////////////////////////////////////////////////
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// Copyright (C) 2017, Carnegie Mellon University and University of Cambridge,
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// all rights reserved.
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//
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// ACADEMIC OR NON-PROFIT ORGANIZATION NONCOMMERCIAL RESEARCH USE ONLY
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//
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// BY USING OR DOWNLOADING THE SOFTWARE, YOU ARE AGREEING TO THE TERMS OF THIS LICENSE AGREEMENT.
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// IF YOU DO NOT AGREE WITH THESE TERMS, YOU MAY NOT USE OR DOWNLOAD THE SOFTWARE.
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//
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// License can be found in OpenFace-license.txt
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//
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// * Any publications arising from the use of this software, including but
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// not limited to academic journal and conference publications, technical
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// reports and manuals, must cite at least one of the following works:
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//
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// OpenFace: an open source facial behavior analysis toolkit
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// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency
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// in IEEE Winter Conference on Applications of Computer Vision, 2016
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//
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// Rendering of Eyes for Eye-Shape Registration and Gaze Estimation
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// Erroll Wood, Tadas Baltrušaitis, Xucong Zhang, Yusuke Sugano, Peter Robinson, and Andreas Bulling
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// in IEEE International. Conference on Computer Vision (ICCV), 2015
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//
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// Cross-dataset learning and person-speci?c normalisation for automatic Action Unit detection
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// Tadas Baltrušaitis, Marwa Mahmoud, and Peter Robinson
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// in Facial Expression Recognition and Analysis Challenge,
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// IEEE International Conference on Automatic Face and Gesture Recognition, 2015
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//
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// Constrained Local Neural Fields for robust facial landmark detection in the wild.
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// Tadas Baltrušaitis, Peter Robinson, and Louis-Philippe Morency.
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// in IEEE Int. Conference on Computer Vision Workshops, 300 Faces in-the-Wild Challenge, 2013.
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//
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///////////////////////////////////////////////////////////////////////////////
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// Parameters of the CLNF, CLM-Z and CLM trackers
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#ifndef __LANDMARK_DETECTOR_PARAM_H
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#define __LANDMARK_DETECTOR_PARAM_H
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#include <vector>
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using namespace std;
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namespace LandmarkDetector
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{
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struct FaceModelParameters
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{
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// A number of RLMS or NU-RLMS iterations
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int num_optimisation_iteration;
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// Should pose be limited to 180 degrees frontal
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bool limit_pose;
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// Should face validation be done
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bool validate_detections;
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// Landmark detection validator boundary for correct detection, the regressor output -1 (perfect alignment) 1 (bad alignment),
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double validation_boundary;
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// Used when tracking is going well
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vector<int> window_sizes_small;
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// Used when initialising or tracking fails
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vector<int> window_sizes_init;
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// Used for the current frame
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vector<int> window_sizes_current;
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// How big is the tracking template that helps with large motions
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double face_template_scale;
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bool use_face_template;
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// Where to load the model from
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string model_location;
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// this is used for the smooting of response maps (KDE sigma)
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double sigma;
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double reg_factor; // weight put to regularisation
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double weight_factor; // factor for weighted least squares
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// should multiple views be considered during reinit
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bool multi_view;
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// How often should face detection be used to attempt reinitialisation, every n frames (set to negative not to reinit)
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int reinit_video_every;
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// 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
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// Also HAAR detector can detect smaller faces while HOG SVM is only capable of detecting faces at least 70px across
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enum FaceDetector{HAAR_DETECTOR, HOG_SVM_DETECTOR};
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string face_detector_location;
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FaceDetector curr_face_detector;
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// Should the results be visualised and reported to console
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bool quiet_mode;
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// Should the model be refined hierarchically (if available)
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bool refine_hierarchical;
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// Should the parameters be refined for different scales
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bool refine_parameters;
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// Using the brand new and experimental gaze tracker
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bool track_gaze;
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FaceModelParameters();
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FaceModelParameters(vector<string> &arguments);
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private:
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void init();
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};
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}
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#endif // __LANDMARK_DETECTOR_PARAM_H
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