opencvc++四个摄像头标定的代码

下面是用OpenCV库进行四个摄像头标定的示例代码，包含了角点提取、摄像头标定和保存标定结果等步骤：

#include <opencv2/opencv.hpp>

using namespace cv;
using namespace std;

int main()
{
    // 设置标定板参数
    Size boardSize(9, 6);
    float squareSize = 2.5; // 单位为厘米
    vector<Point3f> objPoints;
    for (int i = 0; i < boardSize.height; i++)
    {
        for (int j = 0; j < boardSize.width; j++)
        {
            objPoints.push_back(Point3f(j * squareSize, i * squareSize, 0));
        }
    }

    // 获取摄像头图像
    vector<string> cameraNames = {"camera0", "camera1", "camera2", "camera3"};
    vector<VideoCapture> cameras(4);
    for (int i = 0; i < 4; i++)
    {
        cameras[i].open(i);
        if (!cameras[i].isOpened())
        {
            cerr << "Failed to open camera " << i << endl;
            return -1;
        }
    }

    // 提取角点
    vector<vector<Point2f>> imagePoints(4);
    Mat image, gray;
    vector<Point2f> corners;
    namedWindow("Camera", WINDOW_NORMAL);
    for (int i = 0; i < 20; i++)
    {
        for (int j = 0; j < 4; j++)
        {
            cameras[j] >> image;
            cvtColor(image, gray, COLOR_BGR2GRAY);
            bool found = findChessboardCorners(gray, boardSize, corners, CALIB_CB_ADAPTIVE_THRESH | CALIB_CB_NORMALIZE_IMAGE);
            if (found)
            {
                drawChessboardCorners(image, boardSize, corners, found);
                imshow(cameraNames[j], image);
                waitKey(500);
                imagePoints[j].push_back(corners);
            }
        }
    }
    destroyAllWindows();

    // 标定摄像头
    vector<Mat> rvecs, tvecs;
    vector<Mat> cameraMatrix(4), distCoeffs(4);
    for (int i = 0; i < 4; i++)
    {
        calibrateCamera(objPoints, imagePoints[i], image.size(), cameraMatrix[i], distCoeffs[i], rvecs, tvecs);
    }

    // 保存标定结果
    FileStorage fs("calibration.yml", FileStorage::WRITE);
    for (int i = 0; i < 4; i++)
    {
        fs << cameraNames[i] << "{"
           << "cameraMatrix" << cameraMatrix[i]
           << "distCoeffs" << distCoeffs[i]
           << "}";
    }
    fs.release();

    return 0;
}

在以上代码中，我们首先设置了标定板参数和摄像头名称，然后通过循环获取每个摄像头的图像，并对图像进行角点提取。接着，我们利用得到的角点和标定板参数，对每个摄像头进行标定，得到内参矩阵和畸变系数。最后，将标定结果保存到文件中。