refinepoints.cpp

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#include "Common.h"


using namespace std;
using namespace cv;

/*refines detected keypoints by choosing matches lesser than an error threshold and normalizes them multiplying with Kinvs*/
void refinepoints(vector<vector<Point2d>>& keypts,vector<vector<DMatch>>& goodmatches,
    vector<vector<Point2d>>& targetkey,vector<vector<Point2d>>& sourcekey,double size[])
{    
    int numberofimages=8;
    //double k[3][3]={{0.0010,0,-0.4471},{0,0.0010,-0.3353},{0,0,1}};

    /*int height=684,width=912;*/
    double k[3][3]={{1020,0,(double)0.5*size[1]},{0,1020,(double)0.5*size[0]},{0,0,1}};
    Mat K(3,3,CV_64F,k);
   /* cout<<K.inv();*/
	cout<<"Normalizing Keypoints..."<<"\n";
    /*normalizing co-ordinates by multiplying with Kinv */
    for( int j=0;j<numberofimages;j++)
    {
        if (j!=3)
        {
            for( int i=0;i<goodmatches.at(j).size();i++)
            {	
                Point2d temp;
                Mat t(3,1,CV_64F);
                t.at<double>(0)=keypts.at(3).at(goodmatches.at(j).at(i).queryIdx).x;
                t.at<double>(1)=keypts.at(3).at(goodmatches.at(j).at(i).queryIdx).y;
                t.at<double>(2)=1;
				/*Normalizing points*/
                t=K.inv()*t;
                temp.x=t.at<double>(0);
                temp.y=t.at<double>(1);
                sourcekey.at(j).push_back(temp);
                t.at<double>(0)=keypts.at(j).at(goodmatches.at(j).at(i).trainIdx).x;
                t.at<double>(1)=keypts.at(j).at(goodmatches.at(j).at(i).trainIdx).y;
                t.at<double>(2)=1;
				/*Normalizing points*/
                t=K.inv()*t;
                temp.x=t.at<double>(0);
                temp.y=t.at<double>(1);
                targetkey.at(j).push_back(temp);
            }

        }
    }
}