opencv实现双目相机标定

双目相机标定是指确定两个相机的内部参数（如焦距、主点位置等）和外部参数（如相对位置、朝向等），以便进行立体视觉处理。OpenCV提供了一组函数来进行双目相机标定，下面是一个简单的示例代码：

#include <opencv2/opencv.hpp>
#include <iostream>

using namespace cv;
using namespace std;

int main()
{
    // 读取标定图像
    Mat img1 = imread("left.png", IMREAD_GRAYSCALE);
    Mat img2 = imread("right.png", IMREAD_GRAYSCALE);

    // 定义标定板参数
    int board_w = 9; // 棋盘格宽度
    int board_h = 6; // 棋盘格高度
    Size board_size(board_w, board_h); // 棋盘格大小

    // 检测棋盘格角点
    vector<Point2f> corners1, corners2;
    bool found1 = findChessboardCorners(img1, board_size, corners1);
    bool found2 = findChessboardCorners(img2, board_size, corners2);

    // 如果角点检测成功
    if (found1 && found2) {
        // 亚像素级角点精确化
        cornerSubPix(img1, corners1, Size(11, 11), Size(-1, -1),
            TermCriteria(TermCriteria::EPS + TermCriteria::MAX_ITER, 30, 0.1));
        cornerSubPix(img2, corners2, Size(11, 11), Size(-1, -1),
            TermCriteria(TermCriteria::EPS + TermCriteria::MAX_ITER, 30, 0.1));

        // 绘制角点
        drawChessboardCorners(img1, board_size, corners1, found1);
        drawChessboardCorners(img2, board_size, corners2, found2);
        imshow("left", img1);
        imshow("right", img2);

        // 标定相机
        vector<vector<Point3f>> object_points(1);
        vector<vector<Point2f>> image_points1(1), image_points2(1);
        vector<Point3f> obj;
        for (int i = 0; i < board_h; i++) {
            for (int j = 0; j < board_w; j++) {
                obj.push_back(Point3f(j * 0.03, i * 0.03, 0));
            }
        }
        object_points[0] = obj;
        image_points1[0] = corners1;
        image_points2[0] = corners2;
        Mat cameraMatrix1, cameraMatrix2, distCoeffs1, distCoeffs2;
        Mat R, T, E, F;
        stereoCalibrate(object_points, image_points1, image_points2,
            cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2,
            img1.size(), R, T, E, F, CALIB_FIX_INTRINSIC);

        // 输出标定结果
        cout << "cameraMatrix1:" << endl << cameraMatrix1 << endl;
        cout << "distCoeffs1:" << endl << distCoeffs1 << endl;
        cout << "cameraMatrix2:" << endl << cameraMatrix2 << endl;
        cout << "distCoeffs2:" << endl << distCoeffs2 << endl;
        cout << "R:" << endl << R << endl;
        cout << "T:" << endl << T << endl;
        cout << "E:" << endl << E << endl;
        cout << "F:" << endl << F << endl;
    }

    waitKey(0);
    return 0;
}

首先，我们读取了左右相机的标定图像，然后定义了棋盘格的大小和参数。接着，我们使用OpenCV的`findChessboardCorners`函数检测棋盘格角点，并使用`cornerSubPix`函数对角点进行精确化。然后，我们绘制了检测到的角点，并使用`stereoCalibrate`函数进行相机标定。最后，我们输出了标定结果。

需要注意的是，在实际应用中，我们需要采集多组不同的标定图像，并对每组图像进行双目相机标定，然后取平均值作为最终的标定结果。此外，还需要对标定结果进行评估，以确保标定的精度和稳定性。