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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. // /////////////////////////////////////////////////////////////////////////////// // Parameters of the CLNF, CLM-Z and CLM trackers #ifndef __LANDMARK_DETECTOR_PARAM_H #define __LANDMARK_DETECTOR_PARAM_H #include 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 window_sizes_small; // Used when initialising or tracking fails vector window_sizes_init; // Used for the current frame vector 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 &arguments); private: void init(); }; } #endif // __LANDMARK_DETECTOR_PARAM_H