samples/cpp/tutorial_code/features2D/Homography/pose_from_homography.cpp

一个关于从共面点估计姿态的示例程序

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#include <iostream>
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/calib3d.hpp>
#include <opencv2/highgui.hpp>
 
using namespace std;
using namespace cv;
 
命名空间
{
enum Pattern { CHESSBOARD, CIRCLES_GRID, ASYMMETRIC_CIRCLES_GRID };
 
void calcChessboardCorners(Size boardSize, float squareSize, vector<Point3f>& corners, Pattern patternType = CHESSBOARD)
{
corners.resize(0);
 
    switch (patternType)
    {
    case CHESSBOARD
    case CIRCLES_GRID
        for( int i = 0; i < boardSize.height; i++ )
            for( int j = 0; j < boardSize.width; j++ )
corners.push_back(Point3f(float(j*squareSize),
                                          float(i*squareSize), 0));
        break;
 
    case ASYMMETRIC_CIRCLES_GRID
        for( int i = 0; i < boardSize.height; i++ )
            for( int j = 0; j < boardSize.width; j++ )
corners.push_back(Point3f(float((2*j + i % 2)*squareSize),
                                          float(i*squareSize), 0));
        break;
 
    default:
        CV_Error(Error::StsBadArg, "未知模式类型\n");
    }
}
 
void poseEstimationFromCoplanarPoints(const string &imgPath, const string &intrinsicsPath, const Size &patternSize,
                                             const float squareSize)
{
    Mat img = imread( samples::findFile( imgPath) );
    Mat img_corners = img.clone(), img_pose = img.clone();
 
vector<Point2f> corners;
    bool found = findChessboardCorners(img, patternSize, corners);
 
    if (!found)
    {
cout << "找不到棋盘格角点。" << endl;
        return;
    }
drawChessboardCorners(img_corners, patternSize, corners, found);
imshow("棋盘格角点检测", img_corners);
 
vector<Point3f> objectPoints;
calcChessboardCorners(patternSize, squareSize, objectPoints);
vector<Point2f> objectPointsPlanar;
    for (size_t i = 0; i < objectPoints.size(); i++)
    {
objectPointsPlanar.push_back(Point2f(objectPoints[i].x, objectPoints[i].y));
    }
 
    FileStorage fs( samples::findFile( intrinsicsPath ), FileStorage::READ);
    Mat cameraMatrix, distCoeffs;
fs["camera_matrix"] >> cameraMatrix;
fs["distortion_coefficients"] >> distCoeffs;
 
vector<Point2f> imagePoints;
undistortPoints(corners, imagePoints, cameraMatrix, distCoeffs);
 
    Mat H = findHomography(objectPointsPlanar, imagePoints);
cout << "H:\n" << H << endl;
 
    // 归一化以确保 ||c1|| = 1
    double norm = sqrt(H.at<double>(0,0)*H.at<double>(0,0) +
H.at<double>(1,0)*H.at<double>(1,0) +
H.at<double>(2,0)*H.at<double>(2,0));
 
H /= norm;
    Mat c1 = H.col(0);
    Mat c2 = H.col(1);
    Mat c3 = c1.cross(c2);
 
    Mat tvec = H.col(2);
    Mat R(3, 3, CV_64F);
 
    for (int i = 0; i < 3; i++)
    {
R.at<double>(i,0) = c1.at<double>(i,0);
R.at<double>(i,1) = c2.at<double>(i,0);
R.at<double>(i,2) = c3.at<double>(i,0);
    }
 
cout << "R（极分解前）：\n" << R << "\ndet(R): " << determinant(R) << endl;
    Mat_<double> W, U, Vt;
SVDecomp(R, W, U, Vt);
R = U*Vt;
    double det = determinant(R);
    if (det < 0)
    {
Vt.at<double>(2,0) *= -1;
Vt.at<double>(2,1) *= -1;
Vt.at<double>(2,2) *= -1;
 
R = U*Vt;
    }
cout << "R（极分解后）：\n" << R << "\ndet(R): " << determinant(R) << endl;
 
    Mat rvec;
Rodrigues(R, rvec);
drawFrameAxes(img_pose, cameraMatrix, distCoeffs, rvec, tvec, 2*squareSize);
imshow("从共面点估计姿态", img_pose);
waitKey();
}
 
const char* params
= "{ help h | | print usage }"
      "{ image | left04.jpg | 棋盘图像路径 }"
      "{ intrinsics | left_intrinsics.yml | 相机内参路径 }"
      "{ width bw | 9 | 棋盘宽度 }"
      "{ height bh | 6 | 棋盘高度 }"
      "{ square_size | 0.025 | 棋盘方格大小 }";
}
 
int main(int argc, char *argv[])
{
    CommandLineParser parser(argc, argv, params);
 
    if (parser.has("help"))
    {
parser.about("单应性教程代码。\n"
            "示例 1：使用共面点从单应性计算姿态。\n");
parser.printMessage();
        return 0;
    }
 
    Size patternSize(parser.get<int>("width"), parser.get<int>("height"));
    float squareSize = (float) parser.get<double>("square_size");
poseEstimationFromCoplanarPoints(parser.get<String>("image"),
parser.get<String>("intrinsics"),
patternSize, squareSize);
 
    return 0;
}