c++ - OpenCV findHomography 断言失败错误

Question

我正在尝试构建 OpenCV 附带的示例程序 brief_match_test.cpp，但是当我运行该程序时，我不断从 cv::findHomography() 函数中收到此错误:

OpenCV Error: Assertion failed (mtype == type0 || (CV_MAT_CN(mtype) == CV_MAT_CN(type0) && ((1 << type0) & fixedDepthMask) != 0)) in create, file /opt/local/var/macports/build/_opt_local_var_macports_sources_rsync.macports.org_release_tarballs_ports_graphics_opencv/opencv/work/OpenCV-2.4.3/modules/core/src/matrix.cpp, line 1421
libc++abi.dylib: terminate called throwing an exception
findHomography ... Abort trap: 6

我是这样编译的:

g++ `pkg-config --cflags opencv` `pkg-config --libs opencv` brief_match_test.cpp -o brief_match_test

我已经在程序中添加了一些内容来显示 FAST 算法找到的关键点，但还没有触及处理单应性的部分。我将包括我修改过的示例，以防万一我搞砸了:

/*
 * matching_test.cpp
 *
 *  Created on: Oct 17, 2010
 *      Author: ethan
 */
#include "opencv2/core/core.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <vector>
#include <iostream>

using namespace cv;
using namespace std;

//Copy (x,y) location of descriptor matches found from KeyPoint data structures into Point2f vectors
static void matches2points(const vector<DMatch>& matches, const vector<KeyPoint>& kpts_train,
                    const vector<KeyPoint>& kpts_query, vector<Point2f>& pts_train, vector<Point2f>& pts_query)
{
  pts_train.clear();
  pts_query.clear();
  pts_train.reserve(matches.size());
  pts_query.reserve(matches.size());
  for (size_t i = 0; i < matches.size(); i++)
  {
    const DMatch& match = matches[i];
    pts_query.push_back(kpts_query[match.queryIdx].pt);
    pts_train.push_back(kpts_train[match.trainIdx].pt);
  }

}

static double match(const vector<KeyPoint>& /*kpts_train*/, const vector<KeyPoint>& /*kpts_query*/, DescriptorMatcher& matcher,
            const Mat& train, const Mat& query, vector<DMatch>& matches)
{

  double t = (double)getTickCount();
  matcher.match(query, train, matches); //Using features2d
  return ((double)getTickCount() - t) / getTickFrequency();
}

static void help()
{
       cout << "This program shows how to use BRIEF descriptor to match points in features2d" << endl <<
               "It takes in two images, finds keypoints and matches them displaying matches and final homography warped results" << endl <<
                "Usage: " << endl <<
                    "image1 image2 " << endl <<
                "Example: " << endl <<
                    "box.png box_in_scene.png " << endl;
}

const char* keys =
{
    "{1|  |box.png               |the first image}"
    "{2|  |box_in_scene.png|the second image}"
};

int main(int argc, const char ** argv)
{
    Mat outimg;
    help();
    CommandLineParser parser(argc, argv, keys);
    string im1_name = parser.get<string>("1");
    string im2_name = parser.get<string>("2");

    Mat im1 = imread(im1_name, CV_LOAD_IMAGE_GRAYSCALE);
    Mat im2 = imread(im2_name, CV_LOAD_IMAGE_GRAYSCALE);

    if (im1.empty() || im2.empty())
    {
      cout << "could not open one of the images..." << endl;
      cout << "the cmd parameters have next current value: " << endl;
      parser.printParams();
      return 1;
    }

    double t = (double)getTickCount();

    FastFeatureDetector detector(15);
    BriefDescriptorExtractor extractor(32); //this is really 32 x 8 matches since they are binary matches packed into bytes

    vector<KeyPoint> kpts_1, kpts_2;
    detector.detect(im1, kpts_1);
    detector.detect(im2, kpts_2);

    t = ((double)getTickCount() - t) / getTickFrequency();

    cout << "found " << kpts_1.size() << " keypoints in " << im1_name << endl << "fount " << kpts_2.size()
        << " keypoints in " << im2_name << endl << "took " << t << " seconds." << endl;

    drawKeypoints(im1, kpts_1, outimg, 200);
    imshow("Keypoints - Image1", outimg);
    drawKeypoints(im2, kpts_2, outimg, 200);
    imshow("Keypoints - Image2", outimg);

    Mat desc_1, desc_2;

    cout << "computing descriptors..." << endl;

    t = (double)getTickCount();

    extractor.compute(im1, kpts_1, desc_1);
    extractor.compute(im2, kpts_2, desc_2);

    t = ((double)getTickCount() - t) / getTickFrequency();

    cout << "done computing descriptors... took " << t << " seconds" << endl;

    //Do matching using features2d
    cout << "matching with BruteForceMatcher<Hamming>" << endl;
    BFMatcher matcher_popcount(NORM_HAMMING);
    vector<DMatch> matches_popcount;
    double pop_time = match(kpts_1, kpts_2, matcher_popcount, desc_1, desc_2, matches_popcount);
    cout << "done BruteForceMatcher<Hamming> matching. took " << pop_time << " seconds" << endl;

    vector<Point2f> mpts_1, mpts_2;
    cout << "matches2points ... ";
    matches2points(matches_popcount, kpts_1, kpts_2, mpts_1, mpts_2); //Extract a list of the (x,y) location of the matches
    cout << "done" << endl;

    vector<char> outlier_mask;
    cout << "findHomography ... ";
    Mat H = findHomography(mpts_2, mpts_1, RANSAC, 1, outlier_mask);
    cout << "done" << endl;

    cout << "drawMatches ... ";
    drawMatches(im2, kpts_2, im1, kpts_1, matches_popcount, outimg, Scalar::all(-1), Scalar::all(-1), outlier_mask);
    cout << "done" << endl;
    imshow("matches - popcount - outliers removed", outimg);

    Mat warped;
    Mat diff;
    warpPerspective(im2, warped, H, im1.size());
    imshow("warped", warped);
    absdiff(im1,warped,diff);
    imshow("diff", diff);
    waitKey();
    return 0;
}

Answer 1

我不确定，所以我真的要回答这个问题，因为到目前为止还没有其他人回答过这个问题，而且距您提出这个问题已经 10 个小时了。

我的第一个想法是您没有足够的点对。一个单应性至少需要4对，否则找不到唯一解。您可能需要确保仅在匹配项数量至少为 4 时才调用 findHomography。

或者，问题here和 here是关于相同的失败断言(虽然是由调用与您不同的函数引起的)。我猜 OpenCV 会进行某种形式的动态类型检查或模板化，这样本应在编译时发生的类型不匹配错误最终会以断言失败的形式成为运行时错误。综上所述，也许您应该在传递给 findHomography 之前将 mpts_1 和 mpts_2 转换为 cv::Mat。