/////////////////////////////////////////////////////////////////////////////// // Copyright (C) 2017, Carnegie Mellon University and University of Cambridge, // all rights reserved. // // ACADEMIC OR NON-PROFIT ORGANIZATION NONCOMMERCIAL RESEARCH USE ONLY // // BY USING OR DOWNLOADING THE SOFTWARE, YOU ARE AGREEING TO THE TERMS OF THIS LICENSE AGREEMENT. // IF YOU DO NOT AGREE WITH THESE TERMS, YOU MAY NOT USE OR DOWNLOAD THE SOFTWARE. // // License can be found in OpenFace-license.txt // // * 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 __PDM_h_ #define __PDM_h_ // OpenCV includes #include #include "LandmarkDetectorParameters.h" namespace LandmarkDetector { //=========================================================================== // A linear 3D Point Distribution Model (constructed using Non-Rigid structure from motion or PCA) // Only describes the model but does not contain an instance of it (no local or global parameters are stored here) // Contains the utility functions to help manipulate the model class PDM{ public: // The 3D mean shape vector of the PDM [x1,..,xn,y1,...yn,z1,...,zn] cv::Mat_ mean_shape; // Principal components or variation bases of the model, cv::Mat_ princ_comp; // Eigenvalues (variances) corresponding to the bases cv::Mat_ eigen_values; PDM(){;} // A copy constructor PDM(const PDM& other); void Read(string location); // Number of vertices inline int NumberOfPoints() const {return mean_shape.rows/3;} // Listing the number of modes of variation inline int NumberOfModes() const {return princ_comp.cols;} void Clamp(cv::Mat_& params_local, cv::Vec6d& params_global, const FaceModelParameters& params); // Compute shape in object space (3D) void CalcShape3D(cv::Mat_& out_shape, const cv::Mat_& params_local) const; // Compute shape in image space (2D) void CalcShape2D(cv::Mat_& out_shape, const cv::Mat_& params_local, const cv::Vec6d& params_global) const; // provided the bounding box of a face and the local parameters (with optional rotation), generates the global parameters that can generate the face with the provided bounding box void CalcParams(cv::Vec6d& out_params_global, const cv::Rect_& bounding_box, const cv::Mat_& params_local, const cv::Vec3d rotation = cv::Vec3d(0.0)); // Provided the landmark location compute global and local parameters best fitting it (can provide optional rotation for potentially better results) void CalcParams(cv::Vec6d& out_params_global, const cv::Mat_& out_params_local, const cv::Mat_& landmark_locations, const cv::Vec3d rotation = cv::Vec3d(0.0)); // provided the model parameters, compute the bounding box of a face void CalcBoundingBox(cv::Rect& out_bounding_box, const cv::Vec6d& params_global, const cv::Mat_& params_local); // Helpers for computing Jacobians, and Jacobians with the weight matrix void ComputeRigidJacobian(const cv::Mat_& params_local, const cv::Vec6d& params_global, cv::Mat_ &Jacob, const cv::Mat_ W, cv::Mat_ &Jacob_t_w); void ComputeJacobian(const cv::Mat_& params_local, const cv::Vec6d& params_global, cv::Mat_ &Jacobian, const cv::Mat_ W, cv::Mat_ &Jacob_t_w); // Given the current parameters, and the computed delta_p compute the updated parameters void UpdateModelParameters(const cv::Mat_& delta_p, cv::Mat_& params_local, cv::Vec6d& params_global); }; //=========================================================================== } #endif