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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. // /////////////////////////////////////////////////////////////////////////////// // Header for all external CLM/CLNF/CLM-Z methods of interest to the user // // #ifndef __LANDMARK_DETECTOR_FUNC_h_ #define __LANDMARK_DETECTOR_FUNC_h_ // OpenCV includes #include #include #include #include using namespace std; namespace LandmarkDetector { //================================================================================================================ // Landmark detection in videos, need to provide an image and model parameters (default values work well) // Optionally can provide a bounding box from which to start tracking //================================================================================================================ bool DetectLandmarksInVideo(const cv::Mat_ &grayscale_image, CLNF& clnf_model, FaceModelParameters& params); bool DetectLandmarksInVideo(const cv::Mat_ &grayscale_image, const cv::Mat_ &depth_image, CLNF& clnf_model, FaceModelParameters& params); bool DetectLandmarksInVideo(const cv::Mat_ &grayscale_image, const cv::Rect_ bounding_box, CLNF& clnf_model, FaceModelParameters& params); bool DetectLandmarksInVideo(const cv::Mat_ &grayscale_image, const cv::Mat_ &depth_image, const cv::Rect_ bounding_box, CLNF& clnf_model, FaceModelParameters& params); //================================================================================================================ // Landmark detection in image, need to provide an image and optionally CLNF model together with parameters (default values work well) // Optionally can provide a bounding box in which detection is performed (this is useful if multiple faces are to be detected in images) //================================================================================================================ bool DetectLandmarksInImage(const cv::Mat_ &grayscale_image, CLNF& clnf_model, FaceModelParameters& params); // Providing a bounding box bool DetectLandmarksInImage(const cv::Mat_ &grayscale_image, const cv::Rect_ bounding_box, CLNF& clnf_model, FaceModelParameters& params); //================================================ // CLM-Z versions bool DetectLandmarksInImage(const cv::Mat_ &grayscale_image, const cv::Mat_ depth_image, CLNF& clnf_model, FaceModelParameters& params); bool DetectLandmarksInImage(const cv::Mat_ &grayscale_image, const cv::Mat_ depth_image, const cv::Rect_ bounding_box, CLNF& clnf_model, FaceModelParameters& params); //================================================================ // Helper function for getting head pose from CLNF parameters // Return the current estimate of the head pose, this can be either in camera or world coordinate space // The format returned is [Tx, Ty, Tz, Eul_x, Eul_y, Eul_z] cv::Vec6d GetPoseCamera(const CLNF& clnf_model, double fx, double fy, double cx, double cy); cv::Vec6d GetPoseWorld(const CLNF& clnf_model, double fx, double fy, double cx, double cy); // Getting a head pose estimate from the currently detected landmarks, with appropriate correction for perspective // This is because rotation estimate under orthographic assumption is only correct close to the centre of the image // These methods attempt to correct for that // The pose returned can be either in camera or world coordinates // The format returned is [Tx, Ty, Tz, Eul_x, Eul_y, Eul_z] cv::Vec6d GetCorrectedPoseCamera(const CLNF& clnf_model, double fx, double fy, double cx, double cy); cv::Vec6d GetCorrectedPoseWorld(const CLNF& clnf_model, double fx, double fy, double cx, double cy); //=========================================================================== } #endif