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我试图从surface_matching开始工作表面匹配示例代码。我能够编译代码，然后在运行时./surface_matching /home/surface_matching/coke.ply /home/surface_matching/01.ply

我运行与链接中相同的代码示例。代码如下

#include "opencv2/surface_matching.hpp"
#include <iostream>
#include "opencv2/surface_matching/ppf_helpers.hpp"
#include "opencv2/core/utility.hpp"

using namespace std;
using namespace cv;
using namespace ppf_match_3d;

static void help(const string& errorMessage)
{
    cout << "Program init error : "<< errorMessage << endl;
    cout << "\nUsage : ppf_matching [input model file] [input scene file]"<< endl;
    cout << "\nPlease start again with new parameters"<< endl;
}

int main(int argc, char** argv)
{
    // welcome message
    cout << "****************************************************" << endl;
    cout << "* Surface Matching demonstration : demonstrates the use of surface matching"
             " using point pair features." << endl;
    cout << "* The sample loads a model and a scene, where the model lies in a different"
             " pose than the training.\n* It then trains the model and searches for it in the"
             " input scene. The detected poses are further refined by ICP\n* and printed to the "
             " standard output." << endl;
    cout << "****************************************************" << endl;
    
    if (argc < 3)
    {
        help("Not enough input arguments");
        exit(1);
    }
    
#if (defined __x86_64__ || defined _M_X64)
    cout << "Running on 64 bits" << endl;
#else
    cout << "Running on 32 bits" << endl;
#endif
    
#ifdef _OPENMP
    cout << "Running with OpenMP" << endl;
#else
    cout << "Running without OpenMP and without TBB" << endl;
#endif
    
    string modelFileName = (string)argv[1];
    string sceneFileName = (string)argv[2];
    
    Mat pc = loadPLYSimple(modelFileName.c_str(), 1);
    
    // Now train the model
    cout << "Training..." << endl;
    int64 tick1 = cv::getTickCount();
    ppf_match_3d::PPF3DDetector detector(0.025, 0.05);
    detector.trainModel(pc);
    int64 tick2 = cv::getTickCount();
    cout << endl << "Training complete in "
         << (double)(tick2-tick1)/ cv::getTickFrequency()
         << " sec" << endl << "Loading model..." << endl;
         
    // Read the scene
    Mat pcTest = loadPLYSimple(sceneFileName.c_str(), 1);
    
    // Match the model to the scene and get the pose
    cout << endl << "Starting matching..." << endl;
    vector<Pose3DPtr> results;
    tick1 = cv::getTickCount();
    // orig detector.match(pcTest, results, 1.0/40.0, 0.05);
    detector.match(pcTest, results, 1.0/40.0, 0.05);
    tick2 = cv::getTickCount();
    cout << endl << "PPF Elapsed Time " <<
         (tick2-tick1)/cv::getTickFrequency() << " sec" << endl;
         
    // Get only first N results
    int N = 2;
    vector<Pose3DPtr> resultsSub(results.begin(),results.begin()+N);
    
    // Create an instance of ICP
    ICP icp(100, 0.005f, 2.5f, 8);
    int64 t1 = cv::getTickCount();
    
    // Register for all selected poses
    cout << endl << "Performing ICP on " << N << " poses..." << endl;
    icp.registerModelToScene(pc, pcTest, resultsSub);
    int64 t2 = cv::getTickCount();
    
    cout << endl << "ICP Elapsed Time " <<
         (t2-t1)/cv::getTickFrequency() << " sec" << endl;
         
    cout << "Poses: " << endl;
    // debug first five poses
    for (size_t i=0; i<resultsSub.size(); i++)
    {
        Pose3DPtr result = resultsSub[i];
        cout << "Pose Result " << i << endl;
        result->printPose();
        if (i==0)
        {
            Mat pct = transformPCPose(pc, result->pose);
            writePLY(pct, "para6700PCTrans.ply");
        }
    }
    
    return 0;
    
}

它运行但从未得到任何结果。我收到了这个错误

$ ./surface_matching /home/admini/surface_matching/coke.ply /home/admini/surface_matching/01.ply 
****************************************************
* Surface Matching demonstration : demonstrates the use of surface matching using point pair features.
* The sample loads a model and a scene, where the model lies in a different pose than the training.
* It then trains the model and searches for it in the input scene. The detected poses are further refined by ICP
* and printed to the  standard output.
****************************************************
Running on 64 bits
Running without OpenMP and without TBB
Training...

Training complete in 0.100169 sec
Loading model...

Starting matching...
Segmentation fault (core dumped)

训练完成并开始匹配，但随后出现分段错误。可能是什么问题？这里的对象模型文件：可乐罐模型 和场景文件 场景文件

可能是什么问题？

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