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9.2 KiB
C++
204 lines
No EOL
9.2 KiB
C++
///////////////////////////////////////////////////////////////////////////////
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// Copyright (C) 2016, Carnegie Mellon University and University of Cambridge,
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// all rights reserved.
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//
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// THIS SOFTWARE IS PROVIDED “AS IS” FOR ACADEMIC USE ONLY AND ANY EXPRESS
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// OR IMPLIED WARRANTIES WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
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// THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS
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// BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY.
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// OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
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// HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
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// STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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// ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Notwithstanding the license granted herein, Licensee acknowledges that certain components
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// of the Software may be covered by so-called “open source” software licenses (“Open Source
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// Components”), which means any software licenses approved as open source licenses by the
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// Open Source Initiative or any substantially similar licenses, including without limitation any
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// license that, as a condition of distribution of the software licensed under such license,
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// requires that the distributor make the software available in source code format. Licensor shall
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// provide a list of Open Source Components for a particular version of the Software upon
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// Licensee’s request. Licensee will comply with the applicable terms of such licenses and to
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// the extent required by the licenses covering Open Source Components, the terms of such
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// licenses will apply in lieu of the terms of this Agreement. To the extent the terms of the
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// licenses applicable to Open Source Components prohibit any of the restrictions in this
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// License Agreement with respect to such Open Source Component, such restrictions will not
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// apply to such Open Source Component. To the extent the terms of the licenses applicable to
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// Open Source Components require Licensor to make an offer to provide source code or
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// related information in connection with the Software, such offer is hereby made. Any request
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// for source code or related information should be directed to cl-face-tracker-distribution@lists.cam.ac.uk
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// Licensee acknowledges receipt of notices for the Open Source Components for the initial
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// delivery of the Software.
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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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#include "opencv2/core/core.hpp"
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#include "opencv2/imgproc/imgproc.hpp"
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#include "opencv2/calib3d/calib3d.hpp"
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#include <iostream>
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#include "GazeEstimation.h"
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using namespace std;
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using namespace FaceAnalysis;
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// For subpixel accuracy drawing
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const int gaze_draw_shiftbits = 4;
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const int gaze_draw_multiplier = 1 << 4;
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cv::Point3f RaySphereIntersect(cv::Point3f rayOrigin, cv::Point3f rayDir, cv::Point3f sphereOrigin, float sphereRadius){
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float dx = rayDir.x;
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float dy = rayDir.y;
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float dz = rayDir.z;
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float x0 = rayOrigin.x;
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float y0 = rayOrigin.y;
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float z0 = rayOrigin.z;
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float cx = sphereOrigin.x;
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float cy = sphereOrigin.y;
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float cz = sphereOrigin.z;
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float r = sphereRadius;
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float a = dx*dx + dy*dy + dz*dz;
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float b = 2*dx*(x0-cx) + 2*dy*(y0-cy) + 2*dz*(z0-cz);
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float c = cx*cx + cy*cy + cz*cz + x0*x0 + y0*y0 + z0*z0 + -2*(cx*x0 + cy*y0 + cz*z0) - r*r;
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float disc = b*b - 4*a*c;
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float t = (-b - sqrt(b*b - 4*a*c))/2*a;
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// This implies that the lines did not intersect, point straight ahead
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if (b*b - 4 * a*c < 0)
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return cv::Point3f(0, 0, -1);
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return rayOrigin + rayDir * t;
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}
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cv::Point3f GetPupilPosition(cv::Mat_<double> eyeLdmks3d){
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eyeLdmks3d = eyeLdmks3d.t();
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cv::Mat_<double> irisLdmks3d = eyeLdmks3d.rowRange(0,8);
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cv::Point3f p (mean(irisLdmks3d.col(0))[0], mean(irisLdmks3d.col(1))[0], mean(irisLdmks3d.col(2))[0]);
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return p;
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}
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void FaceAnalysis::EstimateGaze(const LandmarkDetector::CLNF& clnf_model, cv::Point3f& gaze_absolute, float fx, float fy, float cx, float cy, bool left_eye)
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{
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cv::Vec6d headPose = LandmarkDetector::GetPoseCamera(clnf_model, fx, fy, cx, cy);
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cv::Vec3d eulerAngles(headPose(3), headPose(4), headPose(5));
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cv::Matx33d rotMat = LandmarkDetector::Euler2RotationMatrix(eulerAngles);
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int part = -1;
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for (size_t i = 0; i < clnf_model.hierarchical_models.size(); ++i)
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{
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if (left_eye && clnf_model.hierarchical_model_names[i].compare("left_eye_28") == 0)
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{
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part = i;
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}
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if (!left_eye && clnf_model.hierarchical_model_names[i].compare("right_eye_28") == 0)
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{
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part = i;
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}
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}
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if (part == -1)
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{
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std::cout << "Couldn't find the eye model, something wrong" << std::endl;
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}
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cv::Mat eyeLdmks3d = clnf_model.hierarchical_models[part].GetShape(fx, fy, cx, cy);
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cv::Point3f pupil = GetPupilPosition(eyeLdmks3d);
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cv::Point3f rayDir = pupil / norm(pupil);
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cv::Mat faceLdmks3d = clnf_model.GetShape(fx, fy, cx, cy);
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faceLdmks3d = faceLdmks3d.t();
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cv::Mat offset = (cv::Mat_<double>(3, 1) << 0, -3.50, 0);
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int eyeIdx = 1;
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if (left_eye)
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{
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eyeIdx = 0;
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}
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cv::Mat eyeballCentreMat = (faceLdmks3d.row(36+eyeIdx*6) + faceLdmks3d.row(39+eyeIdx*6))/2.0f + (cv::Mat(rotMat)*offset).t();
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cv::Point3f eyeballCentre = cv::Point3f(eyeballCentreMat);
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cv::Point3f gazeVecAxis = RaySphereIntersect(cv::Point3f(0,0,0), rayDir, eyeballCentre, 12) - eyeballCentre;
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gaze_absolute = gazeVecAxis / norm(gazeVecAxis);
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}
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void FaceAnalysis::DrawGaze(cv::Mat img, const LandmarkDetector::CLNF& clnf_model, cv::Point3f gazeVecAxisLeft, cv::Point3f gazeVecAxisRight, float fx, float fy, float cx, float cy)
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{
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cv::Mat cameraMat = (cv::Mat_<double>(3, 3) << fx, 0, cx, 0, fy, cy, 0, 0, 0);
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int part_left = -1;
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int part_right = -1;
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for (size_t i = 0; i < clnf_model.hierarchical_models.size(); ++i)
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{
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if (clnf_model.hierarchical_model_names[i].compare("left_eye_28") == 0)
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{
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part_left = i;
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}
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if (clnf_model.hierarchical_model_names[i].compare("right_eye_28") == 0)
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{
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part_right = i;
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}
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}
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cv::Mat eyeLdmks3d_left = clnf_model.hierarchical_models[part_left].GetShape(fx, fy, cx, cy);
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cv::Point3f pupil_left = GetPupilPosition(eyeLdmks3d_left);
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cv::Mat eyeLdmks3d_right = clnf_model.hierarchical_models[part_right].GetShape(fx, fy, cx, cy);
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cv::Point3f pupil_right = GetPupilPosition(eyeLdmks3d_right);
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vector<cv::Point3d> points_left;
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points_left.push_back(cv::Point3d(pupil_left));
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points_left.push_back(cv::Point3d(pupil_left + gazeVecAxisLeft*50.0));
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vector<cv::Point3d> points_right;
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points_right.push_back(cv::Point3d(pupil_right));
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points_right.push_back(cv::Point3d(pupil_right + gazeVecAxisRight*50.0));
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cv::Mat_<double> proj_points;
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cv::Mat_<double> mesh_0 = (cv::Mat_<double>(2, 3) << points_left[0].x, points_left[0].y, points_left[0].z, points_left[1].x, points_left[1].y, points_left[1].z);
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LandmarkDetector::Project(proj_points, mesh_0, fx, fy, cx, cy);
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cv::line(img, cv::Point(cvRound(proj_points.at<double>(0,0) * (double)gaze_draw_multiplier), cvRound(proj_points.at<double>(0, 1) * (double)gaze_draw_multiplier)),
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cv::Point(cvRound(proj_points.at<double>(1, 0) * (double)gaze_draw_multiplier), cvRound(proj_points.at<double>(1, 1) * (double)gaze_draw_multiplier)), cv::Scalar(110, 220, 0), 2, CV_AA, gaze_draw_shiftbits);
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cv::Mat_<double> mesh_1 = (cv::Mat_<double>(2, 3) << points_right[0].x, points_right[0].y, points_right[0].z, points_right[1].x, points_right[1].y, points_right[1].z);
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LandmarkDetector::Project(proj_points, mesh_1, fx, fy, cx, cy);
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cv::line(img, cv::Point(cvRound(proj_points.at<double>(0, 0) * (double)gaze_draw_multiplier), cvRound(proj_points.at<double>(0, 1) * (double)gaze_draw_multiplier)),
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cv::Point(cvRound(proj_points.at<double>(1, 0) * (double)gaze_draw_multiplier), cvRound(proj_points.at<double>(1, 1) * (double)gaze_draw_multiplier)), cv::Scalar(110, 220, 0), 2, CV_AA, gaze_draw_shiftbits);
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} |