如何獲得3D座標Dlib中的頭部姿態估計軸C++

Question

Dlib C++可以非常好地檢測標記和估計人臉姿態。但是，如何獲得頭部姿態的三維座標軸方向（x，y，z）？

Answer 1

我還面臨同樣的問題，前一段時間，搜索和找到1-2有用的博客文章，這link會讓你對所涉及的技術的概述，如果你只需要計算三維姿勢在十進制那麼你可以跳過OpenGL渲染部分，但是如果你想直觀地獲得反饋，那麼你也可以嘗試OpenGL，但是我建議你忽略OpenGL作爲初學者的一部分，所以從中提取了最小的工作代碼片段github頁面，會是這個樣子：

// Reading image using OpenCV, you may use dlib as well. 
cv::Mat img = cv::imread(imagePath); 

std::vector<double> rv(3), tv(3); 
cv::Mat rvec(rv),tvec(tv); 
cv::Vec3d eav; 

// Labelling the 3D Points derived from a 3D model of human face. 
// You may replace these points as per your custom 3D head model if any 
std::vector<cv::Point3f > modelPoints; 
modelPoints.push_back(cv::Point3f(2.37427,110.322,21.7776)); // l eye (v 314) 
modelPoints.push_back(cv::Point3f(70.0602,109.898,20.8234)); // r eye (v 0) 
modelPoints.push_back(cv::Point3f(36.8301,78.3185,52.0345)); //nose (v 1879) 
modelPoints.push_back(cv::Point3f(14.8498,51.0115,30.2378)); // l mouth (v 1502) 
modelPoints.push_back(cv::Point3f(58.1825,51.0115,29.6224)); // r mouth (v 695) 
modelPoints.push_back(cv::Point3f(-61.8886f,127.797,-89.4523f)); // l ear (v 2011) 
modelPoints.push_back(cv::Point3f(127.603,126.9,-83.9129f));  // r ear (v 1138) 

// labelling the position of corresponding feature points on the input image. 
std::vector<cv::Point2f> srcImagePoints = {cv::Point2f(442, 442), // left eye 
              cv::Point2f(529, 426), // right eye 
              cv::Point2f(501, 479), // nose 
              cv::Point2f(469, 534), //left lip corner 
              cv::Point2f(538, 521), // right lip corner 
              cv::Point2f(349, 457), // left ear 
              cv::Point2f(578, 415) // right ear}; 


cv::Mat ip(srcImagePoints); 

cv::Mat op = cv::Mat(modelPoints); 
cv::Scalar m = mean(cv::Mat(modelPoints)); 

rvec = cv::Mat(rv); 
double _d[9] = {1,0,0, 
       0,-1,0, 
       0,0,-1}; 
Rodrigues(cv::Mat(3,3,CV_64FC1,_d),rvec); 
tv[0]=0;tv[1]=0;tv[2]=1; 
tvec = cv::Mat(tv); 


double max_d = MAX(img.rows,img.cols); 
double _cm[9] = {max_d,  0, (double)img.cols/2.0, 
       0 , max_d, (double)img.rows/2.0, 
       0 ,  0,     1.0}; 
cv::Mat camMatrix = cv::Mat(3,3,CV_64FC1, _cm); 

double _dc[] = {0,0,0,0}; 
solvePnP(op,ip,camMatrix,cv::Mat(1,4,CV_64FC1,_dc),rvec,tvec,false,CV_EPNP); 

double rot[9] = {0}; 
cv::Mat rotM(3,3,CV_64FC1,rot); 
Rodrigues(rvec,rotM); 
double* _r = rotM.ptr<double>(); 
printf("rotation mat: \n %.3f %.3f %.3f\n%.3f %.3f %.3f\n%.3f %.3f %.3f\n", 
     _r[0],_r[1],_r[2],_r[3],_r[4],_r[5],_r[6],_r[7],_r[8]); 

printf("trans vec: \n %.3f %.3f %.3f\n",tv[0],tv[1],tv[2]); 

double _pm[12] = {_r[0],_r[1],_r[2],tv[0], 
        _r[3],_r[4],_r[5],tv[1], 
        _r[6],_r[7],_r[8],tv[2]}; 

cv::Mat tmp,tmp1,tmp2,tmp3,tmp4,tmp5; 
cv::decomposeProjectionMatrix(cv::Mat(3,4,CV_64FC1,_pm),tmp,tmp1,tmp2,tmp3,tmp4,tmp5,eav); 
printf("Face Rotation Angle: %.5f %.5f %.5f\n",eav[0],eav[1],eav[2]); 

輸出：

     **X**  **Y** **Z** 

Face Rotation Angle: 171.44027 -8.72583 -9.90596