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我正在阅读 Mastering OpenCV 一书中的第 4 章的“运动结构”。我目前正在尝试Essential Matrix使用Fundamental Matrix. 此语句 Mat_<double> E = K.t() * F * K; 导致异常，我无法弄清楚。我假设它的类型不匹配。

#include <opencv2/features2d/features2d.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc_c.h>
#include <opencv2/nonfree/features2d.hpp>
#include <opencv/cv.h>

#include <iostream>
#include <vector>

using namespace cv;
using namespace std; 

int main(int argc, const char** argv)
{
    vector<Mat> images;
    vector<vector<KeyPoint>> imgKeyPts;
    cv::Ptr<cv::FeatureDetector> detector;
    cv::Ptr<cv::DescriptorExtractor> extractor;
    std::vector<cv::Mat> descriptors;


    char* imgs[] = {
        {"TestBranches/branches1.jpg"},
        {"TestBranches/branches2.jpg"},
    };

    //Images are already in CV_8UC3 format.
    //No to convert them explicitly for now
    for(int i = 0 ; i < 2; i++)
    {
        Mat im = imread(imgs[i]);
        Mat gray = cv::Mat();
        cvtColor(im, gray, CV_BGR2GRAY);
        images.push_back(gray);
    }

    /* Load Camera's Calibrated Properties */ 
    cv::Mat camMatrix; 
    cv::Mat distortionCamera, distcoeff_32f;
    cv::Mat K, K_32f;
cv::Mat Kinv;           //TODO: Kinv was originally cv::Mat_<double> this data type was not useful     when doing invert operation because it was throwing exceptions. 

    CvMat *intrinsic = (CvMat*)cvLoad( "Intrinsics.xml" );
    CvMat *distortion = (CvMat*)cvLoad( "Distortion.xml" );

    camMatrix = Mat(intrinsic);
    distortionCamera = Mat(distortion);

    cout<<"K = " <<camMatrix<<std::endl;
    cout<<"Distort = "<<distortionCamera<<std::endl;

    K = camMatrix; 
    invert(K, Kinv);
    distortionCamera.convertTo(distcoeff_32f,CV_32FC1);
    K.convertTo(K_32f, CV_32FC1);
    cout<<"Kinv = " <<Kinv<<std::endl;

    /* Extract Image Features and Match with another view */ 
    detector = FeatureDetector::create("PyramidFAST");
    extractor = DescriptorExtractor::create("ORB");


    detector->detect(images, imgKeyPts);
    extractor->compute(images, imgKeyPts,descriptors);


    BFMatcher matcher(NORM_HAMMING,true);
    std::vector< DMatch > matches;
    const Mat& descriptors_1 = descriptors[0];
    const Mat& descriptors_2 = descriptors[1];

    /* Store correspondences in a matrix */ 
    matcher.match( descriptors_1, descriptors_2, matches);

    Mat img_matches, img_1, img_2;

    drawKeypoints(images[0], imgKeyPts[0], img_1);
    drawKeypoints(images[1], imgKeyPts[1], img_2);


    drawMatches( images[0], imgKeyPts[0], images[1], imgKeyPts[1],
        matches, img_matches, Scalar::all(-1), Scalar::all(-1),
        vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );  

    //Outputting point correspondences. 
    imwrite("output.jpg", img_matches);
    imwrite("img1.jpg", img_1);
    imwrite("img2.jpg", img_2);


    vector <Point2f>    imgPts1, imgPts2;

    for( unsigned int i = 0; i < matches.size(); i++)
    {
        //queryidx -> left image
        imgPts1.push_back(imgKeyPts[0][matches[i].queryIdx].pt);
        //trainidx -> right image
        imgPts2.push_back(imgKeyPts[1][matches[i].trainIdx].pt);
    }


    Mat F = findFundamentalMat(imgPts1, imgPts2, FM_RANSAC, 0.1, 0.99);

    cout<<"F type " << CV_MAT_TYPE(F.type())<<endl;
    cout<<"K type " << K.type()<<endl;
    cout<<"K inv type " << Kinv.type()<<endl;
    cout<<"K t type "<< (K.t()).type()<<endl;

    Mat_<double> E = K.t() * F * K;


    cin.get();  
    return 0;
}
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