Ask Your Question
1

findEssentialMat give different results according to the number of feature points [closed]

asked 2017-05-09 12:30:09 -0600

mnchapel gravatar image

updated 2017-05-11 05:21:19 -0600

Hello,

I use the findEssentialMatrix function on a set of feature points (~ 1200 points) and then I use triangulatePoints function to recover the 3D positions of those feature points. But I have a problem with the findEssentialMatrix function because it seems that the result changes according to the number of points.

For example, if I use 1241 points for one frame, the result is quite good (R= 0.5,0.5,0.5 and t=1,0,0) and if I remove only one point the result is totally different (R=3.0,2.0,2.0 and t=0,0,1). I tried to remove other feature points and sometimes it works and sometimes not. I don't understand why. Is there a reason for that ?

std::vector<cv::Point2d> static_feature_point_t;
std::vector<cv::Point2d> static_feature_point_tmdelta;

// read from file
cv::FileStorage fs_t("static_feature_point_t.yml", cv::FileStorage::READ);
cv::FileStorage fs_tmdelta("static_feature_point_tmdelta.yml", cv::FileStorage::READ);

cv::FileNode feature_point_t       = fs_t["feature_point"];
cv::FileNode feature_point_tmdelta = fs_tmdelta["feature_point"];

read(feature_point_t, static_feature_point_t);
read(feature_point_tmdelta, static_feature_point_tmdelta);

fs_t.release();
fs_tmdelta.release();

double focal = 300.;
cv::Point2d camera_principal_point(320, 240);

cv::Mat essential_matrix = cv::findEssentialMat(static_feature_point_t, static_feature_point_tmdelta, focal, camera_principal_point, cv::LMEDS);

cv::Mat rotation, translation;
cv::recoverPose(essential_matrix, static_feature_point_t, static_feature_point_tmdelta, rotation, translation, focal, camera_principal_point);
cv::Mat rot(3,1,CV_64F);
cv::Rodrigues(rotation, rot);
std::cout << "rotation " << rot*180./M_PI << std::endl;
std::cout << "translation " << translation << std::endl;

The two lists of feature points are here (I didn't find how to upload files on the forum or if it is possible)

Thanks,

edit retag flag offensive reopen merge delete

Closed for the following reason the question is answered, right answer was accepted by mnchapel
close date 2017-05-12 03:24:06.278384

Comments

please post your code with findEssentialMat

LBerger gravatar imageLBerger ( 2017-05-09 12:33:51 -0600 )edit

I added it.

mnchapel gravatar imagemnchapel ( 2017-05-10 03:12:53 -0600 )edit

Did you solve your problem ? can you post data in yml format?

LBerger gravatar imageLBerger ( 2017-05-11 01:25:38 -0600 )edit

No, I didn't. I added data and I changed the code according to the .yml files. If you run the code with all points, it works but if you remove the two last points in static_feature_point_t and static_feature_point_tmdelta, the result is totally different (there are 1241 feature points).

mnchapel gravatar imagemnchapel ( 2017-05-11 05:23:34 -0600 )edit

2 answers

Sort by ยป oldest newest most voted
1

answered 2017-05-12 03:21:29 -0600

mnchapel gravatar image

I took a look at the Opencv Code and it seems that only five points are randomly chosen among all the feature points to compute the essential matrix. So I suppose that the error depends on which points are chosen and cv::RNG::uniform(0,count) is used to choose the points (with count == the number of feature points given to findEssentialMatrix). A priori there is no real solution. I choose randomly six points and if the essential matrix is not good, I compute it again. (Thanks LBerger for your time)

edit flag offensive delete link more

Comments

Yes I miss this too. It is written in doc : Lmeds Least-Median- of-Squares Use StereoCalibrateif you know marker loaction in space or back to levenberg method

LBerger gravatar imageLBerger ( 2017-05-12 03:47:27 -0600 )edit
0

answered 2017-05-11 10:25:32 -0600

LBerger gravatar image

Your problem is in Rodrigues function : It does not give you an angle but a vector You don't need to divide by M_PI and multiply by 180 :Rodrigues vector points along the axis of the rotation, and its magnitude is the tangent of half the angle of the rotation

Results are :

Mean marker distance22.0907
Essai 0 with 1241points
rodrigues [-0.008186903247588993, -0.007724206343463332, -0.007796571200079321]
translation [-0.792428255173678, 0.607350228303508, -0.05641950533350303]
Essai 1 with 1141points
rodrigues [-0.006422562844045941, -0.007930323721579204, -0.007210073468255511]
translation [-0.7848951038350637, 0.6194026473826763, -0.01673428788675164]
Essai 2 with 1051points
rodrigues [-0.007931756116646859, -0.008254818133971985, -0.007837048508731704]
translation [-0.7885528566096911, 0.6133322518870682, -0.04481005610165935]
Essai 3 with 971points
rodrigues [-0.005932638328178316, -0.007302101937579567, -0.006471234288512953]
translation [-0.7865388205016264, 0.6173586807921311, -0.01499810303038783]
Essai 4 with 901points
rodrigues [-0.04190340485114951, -0.05506477514402782, -0.005574481988185056]
translation [0.05958445984982116, -0.03116133096247916, -0.9977367706950827]
Essai 5 with 841points
rodrigues [-0.007732722496448771, -0.008182869208508877, -0.007570432016673033]
translation [-0.7867221935703506, 0.6156568405101853, -0.04510925489156264]
Essai 6 with 791points
rodrigues [-0.006090562167324761, -0.007260625571239707, -0.006922225724916698]
translation [-0.7856904222816165, 0.6181434310759613, -0.02427465659022878]
Essai 7 with 751points
rodrigues [-0.006480131550192582, -0.007292119308853618, -0.006526800541123394]
translation [-0.7906105072805985, 0.6120260023408047, -0.01895252585404144]
Essai 8 with 721points
rodrigues [-0.002347222579832763, -0.007466597396004799, -0.005961284930281934]
translation [-0.7572073975061766, 0.6529732600544519, 0.01621353804029994]
Essai 9 with 701points
rodrigues [-0.006929786646756651, -0.007944380422144397, -0.007456723468566674]
translation [-0.7846584369744524, 0.6189268459772316, -0.0352235235813468]

with this program :

#include<opencv2/opencv.hpp>

using namespace std;
using namespace cv;
#define M_PI acos(-1.0)
int main(int argc, char *argv[])
{
    vector<cv::Point2d> static_feature_point_t;
    std::vector<cv::Point2d> static_feature_point_tmdelta;

    FileStorage f1("static_feature_point_t.yml", FileStorage::READ);
    f1["feature_point"] >> static_feature_point_t;
    f1.release();
    FileStorage f2("static_feature_point_tmdelta.yml", FileStorage::READ);
    f2["feature_point"] >> static_feature_point_tmdelta;
    f2.release();
    Mat x(500, 500, CV_8UC3, Scalar(0, 0, 0));
    Mat y(500, 500, CV_8UC3, Scalar(0, 0, 0));
    double d = 0;
    for (int i = 0; i < static_feature_point_t.size(); i++)
    {
        circle(x, static_feature_point_t[i], 3, Scalar(0, 0, 255));
        circle(y, static_feature_point_tmdelta[i], 3, Scalar(0, 255, 255));
        d += norm(static_feature_point_t[i] - static_feature_point_tmdelta[i]);
    }
    cout << "Mean marker distance" << d / static_feature_point_t.size() << "\n";
    imshow("ptx", x);
    imshow("pty", y);
    waitKey();

    for (int i=0;i<10;i++)
    {
        double focal = 300.;
        cv::Point2d camera_principal_point(320, 240);
        cv::Mat essential_matrix = cv::findEssentialMat(static_feature_point_t, static_feature_point_tmdelta, focal, camera_principal_point, cv::LMEDS);
        cv::Mat rotation=Mat::zeros(3,3,CV_64F), translation=Mat::zeros(3, 1, CV_64F);
        cv::recoverPose(essential_matrix, static_feature_point_t, static_feature_point_tmdelta, rotation, translation, focal, camera_principal_point);
        cv::Mat rot(3, 1, CV_64F);
        cv::Rodrigues(rotation, rot);
        cout << "Essai " << i << " with " << static_feature_point_t.size() << "points\n"; 
        //std::cout << "E " << essential_matrix << std::endl;
        //std::cout << "rotation " << rotation << std::endl;
        std::cout << "rodrigues " << rot.t() << std::endl;
        std::cout << "translation " << translation.t() << std::endl;
        for (int j = i; j < 10; j++)
        {
            static_feature_point_t.erase(static_feature_point_t.begin() + j * 20, static_feature_point_t.begin() + j * 20 + 10);
            static_feature_point_tmdelta.erase(static_feature_point_tmdelta.begin() + j * 20, static_feature_point_tmdelta.begin() + j * 20 + 10);
        }
    }
}
edit flag offensive delete link more

Comments

Thanks for your answer. Actually I didn't see that I misused the Rodrigues function so thank you for that. But if you look at the result of "Essai 4", you can see that there is still a problem about the translation vector. For all the other tests, translation vector is about [-0.8, 0.6, 0.0] and for the Essai 4 [0.0, 0.0, -1].

mnchapel gravatar imagemnchapel ( 2017-05-11 11:29:55 -0600 )edit

Question Tools

1 follower

Stats

Asked: 2017-05-09 12:30:09 -0600

Seen: 2,183 times

Last updated: May 12 '17