分段故障核心已转储

我正在尝试从c++创建一个json文件。使用的代码如下：

    Mat projected = eigenfacesExtraction(fileName);
    ofstream myfile;
    myfile.open ("detection.json");
    myfile << "{n";
    myfile << "t "meta":{n";
    myfile << "t "duration":""<<duration<<"",n";  
    myfile << "t "fileName":""<<fileName<<""n";
    myfile << "},n";
    myfile << "t "num_of_people":""<< faces.size()<<"",n";
    myfile << "t "faces":[n";
    myfile << "t "projected":[" << projected.size <<"] ,n";
    for(int i=0; i<faces.size(); i++){
        if(!faces.empty()){ 
            if(i!= faces.size()-1){
            myfile << "t "coord":" t[" << faces[i].x << ", "<<faces[i].y<< ", "<<      faces[i].width << ", "<<faces[i].height<<"],n";
            myfile << "t "descr":" t[" << projected.at<double>(0,1) << ", "<<projected.at<double>(0,2)<< ", "<<        projected.at<double>(0,3) << ", "<<projected.at<double>(0,4)<<"],n";
            }
            else myfile << "t "coord":" t[" << faces[i].x << ", "<<faces[i].y<< ", "<<     faces[i].width << ", "<<faces[i].height<<"]n";
                 myfile << "t "descr":" t[" << projected.at<double>(0,1) << ", "<<projected.at<double>(0,2)<< ", "<<       projected.at<double>(0,3)<< ", "<<projected.at<double>(0,4)<<"],n";
        }
    }
    myfile << "]n";
    myfile << "}";
    myfile.close();
    cout<< "Detection process exits...."<<endl;
    //imwrite( "/opencvAssets/results/"+fileName, image );
    imwrite("outputCapture.jpeg", image);
    //waitKey(0);
    //imshow("cropped image", croppedFaceImage);

我的程序运行良好，json文件存储正确，并打印消息，但我收到以下消息"Segmentation fault（core dumped）"。当我注释出iwrite命令时，json和cout都不起作用，我再次收到相同的消息。这里出了什么事？？本征面提取函数（可能导致问题）如下：

 Mat Detection::eigenfacesExtraction(string fileName){
    Ptr<FaceRecognizer> model = createEigenFaceRecognizer();
    model->load("eigenfaces.yml"); // Load eigenfaces parameters
    Mat eigenvalues = model->getMat("eigenvalues"); // Eigen values of PCA
    Mat convMat = model->getMat("eigenvectors"); //Convariance matrix which contains eigenvectors
    Mat mean = model->getMat("mean"); // Mean value
    convMat.convertTo(convMat, CV_32F);
    mean.convertTo(mean, CV_32F);
    string path = fileName;
    Mat sample ,pca_ed_sample, resizedSample;
    sample = imread(path, CV_LOAD_IMAGE_GRAYSCALE);
    sample.convertTo(sample, CV_32F);
    resize(sample,resizedSample,Size(60,60),0,0,INTER_LINEAR);
    Mat nu =  resizedSample.reshape(1,3600).t();
    pca_ed_sample = (nu-mean)*(convMat);
    return pca_ed_sample;
}