c++ - 使用 OpenCV 2.3.1 和 C++ 校准单个相机

Question

我正在尝试使用 OpenCV 2.3.1 和 Visual Studio 2010(C++ 控制台应用程序)校准网络摄像头。我正在使用这个类:

class CameraCalibrator{
private:
   std::vector<std::vector<cv::Point3f>> objectPoints;
   std::vector<std::vector<cv::Point2f>> imagePoints;
   //Square Lenght
   float squareLenght;
   //output Matrices
   cv::Mat cameraMatrix; //intrinsic
   cv::Mat distCoeffs;
   //flag to specify how calibration is done
   int flag;
   //used in image undistortion
   cv::Mat map1,map2;
   bool mustInitUndistort;
public:
    CameraCalibrator(): flag(0), squareLenght(36.0), mustInitUndistort(true){};
    int addChessboardPoints(const std::vector<std::string>& filelist,cv::Size& boardSize){
        std::vector<std::string>::const_iterator itImg;
        std::vector<cv::Point2f> imageCorners;
        std::vector<cv::Point3f> objectCorners;
        //initialize the chessboard corners in the chessboard reference frame
        //3d scene points
        for(int i = 0; i<boardSize.height; i++){
            for(int j=0;j<boardSize.width;j++){
                objectCorners.push_back(cv::Point3f(float(i)*squareLenght,float(j)*squareLenght,0.0f));
            }
        }
        //2D Image points:
        cv::Mat image; //to contain chessboard image
        int successes = 0;
        //cv::namedWindow("Chess");
        for(itImg=filelist.begin(); itImg!=filelist.end(); itImg++){
            image = cv::imread(*itImg,0);
            bool found = cv::findChessboardCorners(image, boardSize, imageCorners);
            //cv::drawChessboardCorners(image, boardSize, imageCorners, found);
            //cv::imshow("Chess",image);
            //cv::waitKey(1000);
            cv::cornerSubPix(image, imageCorners, cv::Size(5,5),cv::Size(-1,-1),
                cv::TermCriteria(cv::TermCriteria::MAX_ITER+cv::TermCriteria::EPS,30,0.1));
            //if we have a good board, add it to our data
            if(imageCorners.size() == boardSize.area()){
                addPoints(imageCorners,objectCorners);
                successes++;
            }
        }
        return successes;
    }
    void addPoints(const std::vector<cv::Point2f>& imageCorners,const std::vector<cv::Point3f>& objectCorners){
        //2D image point from one view
        imagePoints.push_back(imageCorners);
        //corresponding 3D scene points
        objectPoints.push_back(objectCorners);
    }
    double calibrate(cv::Size &imageSize){
        mustInitUndistort = true;
        std::vector<cv::Mat> rvecs,tvecs;
        return
            cv::calibrateCamera(objectPoints, //the 3D points
                imagePoints,
                imageSize, 
                cameraMatrix, //output camera matrix
                distCoeffs,
                rvecs,tvecs,
                flag);
    }
    void remap(const cv::Mat &image, cv::Mat &undistorted){
        std::cout << cameraMatrix;
        if(mustInitUndistort){ //called once per calibration
            cv::initUndistortRectifyMap(
                cameraMatrix,
                distCoeffs,
                cv::Mat(),
                cameraMatrix,
                image.size(),
                CV_32FC1,
                map1,map2);
            mustInitUndistort = false;
        }
        //apply mapping functions
        cv::remap(image,undistorted,map1,map2,cv::INTER_LINEAR);
    }
};

我使用了 10 张分辨率为 640x480 的棋盘图像(假设这足以进行校准)。主要功能如下所示:

int main(){
    CameraCalibrator calibrateCam;
    std::vector<std::string> filelist;
    filelist.push_back("img10.jpg");
    filelist.push_back("img09.jpg");
    filelist.push_back("img08.jpg");
    filelist.push_back("img07.jpg");
    filelist.push_back("img06.jpg");
    filelist.push_back("img05.jpg");
    filelist.push_back("img04.jpg");
    filelist.push_back("img03.jpg");
    filelist.push_back("img02.jpg");
    filelist.push_back("img01.jpg");

    cv::Size boardSize(8,6);
    double calibrateError;
    int success;
    success = calibrateCam.addChessboardPoints(filelist,boardSize);
    std::cout<<"Success:" << success << std::endl;
    cv::Size imageSize;
    cv::Mat inputImage, outputImage;
    inputImage = cv::imread("img10.jpg",0);
    outputImage = inputImage.clone();
    imageSize = inputImage.size();
    calibrateError = calibrateCam.calibrate(imageSize);
    std::cout<<"Calibration error:" << calibrateError << std::endl;
    calibrateCam.remap(inputImage,outputImage);
    cv::namedWindow("Original");
    cv::imshow("Original",inputImage);
    cv::namedWindow("Undistorted");
    cv::imshow("Undistorted",outputImage);
    cv::waitKey();
    return 0;
}

一切运行无误。 cameraMatrix 看起来像这样(大约):

685.65 0 365.14
0 686.38 206.98
0 0 1

校准误差为 0.310157，这是可以接受的。

但是当我使用重映射时，输出图像看起来比原始图像更差。这是示例:

原图: ]

未失真图像: ]

所以，问题是，我在校准过程中做错了什么吗？ 10 个不同的棋盘图像是否足以进行校准？你有什么建议吗？

Answer 1

相机矩阵不会消除镜头失真，这 4 个值只是焦距(H 和 V)和图像中心(X 和 Y)

还有另一个 3 或 4 值行矩阵(distCoeffs 在您的代码中)，其中包含镜头映射 - 请参阅 Karl 的答案以获取示例代码