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hello guys, i am working on algorithm based on SURF feature detector, and i need to increase the size of the feature if the object in the frame in getting closer and ignore those features whose size is not changing...

so far i have this code :..

#include <iostream>
#include <stdio.h>
#include <opencv2/opencv.hpp>
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/features2d.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/xfeatures2d.hpp>
#include <opencv2/calib3d.hpp>





using namespace cv;
using namespace std;
using namespace cv::xfeatures2d;

/** @function main */
int main( int argc, char** argv )
{


     VideoCapture cap(0);
     //Mat curr, prev;
     if(!cap.isOpened())return -1;
     Mat frame;
    Mat prevframe;

    while (cap.isOpened()) {
        cap.read(frame);


        // more code goes here which I haven't written here

        frame.copyTo(prevframe); // set previous frame to current frame
        //imshow("Video current", frame);
       // imshow("Videoprevious", frame);

        char key = waitKey(33);
        if (key == 'q')
        {
            break;
        }

  //-- Step 1: Detect the keypoints using SURF Detector
  int minHessian = 100;

  Ptr<SURF> detector = SURF::create( minHessian );
  detector->setHessianThreshold(minHessian);

  std::vector<KeyPoint> keypoints1,keypoints2;
  Mat descriptors_1, descriptors_2;

  detector->detectAndCompute( frame, Mat(), keypoints1, descriptors_1 );
  detector->detectAndCompute( prevframe, Mat(), keypoints2, descriptors_2 );

  //-- Step 2: Matching descriptor vectors using FLANN matcher
  FlannBasedMatcher matcher;
  std::vector< DMatch > matches;
  matcher.match( descriptors_1, descriptors_2, matches );
  double max_dist = 0; double min_dist = 100;

  //-- Quick calculation of max and min distances between keypoints
  for( int i = 0; i < descriptors_1.rows; i++ )
  { double dist = matches[i].distance;
    if( dist < min_dist ) min_dist = dist;
    if( dist > max_dist ) max_dist = dist;
  }

  //-- Draw only "good" matches (i.e. whose distance is less than 2*min_dist,
  //-- or a small arbitary value ( 0.02 ) in the event that min_dist is very
  //-- small)
  //-- PS.- radiusMatch can also be used here.


  std::vector< DMatch > good_matches;
  for( int i = 0; i < descriptors_1.rows; i++ )
  { if( matches[i].distance <= max(2*min_dist, 0.02) )
    { good_matches.push_back( matches[i]);}
  }
  //-- Draw only "good" matches
  Mat img_matches;
  drawMatches( frame, keypoints1, prevframe, keypoints2,
               good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
               vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );

  //-- Show detected matches

  imshow( "Good Matches", img_matches );
  if( (good_matches.size() >=20)){

        for( unsigned int i = 0; i < good_matches.size(); i++ )
        {

        }
  }

    }
    waitKey(0);
    return 0;
}

please help

thanks all

hello guys, i am working on algorithm based on SURF feature detector, and i need to increase the size of the feature if the object in the frame in is getting closer and ignore those features whose size is not changing...

so far i have this code :..

#include <iostream>
#include <stdio.h>
#include <opencv2/opencv.hpp>
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/features2d.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/xfeatures2d.hpp>
#include <opencv2/calib3d.hpp>





using namespace cv;
using namespace std;
using namespace cv::xfeatures2d;

/** @function main */
int main( int argc, char** argv )
{


     VideoCapture cap(0);
     //Mat curr, prev;
     if(!cap.isOpened())return -1;
     Mat frame;
    Mat prevframe;

    while (cap.isOpened()) {
        cap.read(frame);


        // more code goes here which I haven't written here

        frame.copyTo(prevframe); // set previous frame to current frame
        //imshow("Video current", frame);
       // imshow("Videoprevious", frame);

        char key = waitKey(33);
        if (key == 'q')
        {
            break;
        }

  //-- Step 1: Detect the keypoints using SURF Detector
  int minHessian = 100;

  Ptr<SURF> detector = SURF::create( minHessian );
  detector->setHessianThreshold(minHessian);

  std::vector<KeyPoint> keypoints1,keypoints2;
  Mat descriptors_1, descriptors_2;

  detector->detectAndCompute( frame, Mat(), keypoints1, descriptors_1 );
  detector->detectAndCompute( prevframe, Mat(), keypoints2, descriptors_2 );

  //-- Step 2: Matching descriptor vectors using FLANN matcher
  FlannBasedMatcher matcher;
  std::vector< DMatch > matches;
  matcher.match( descriptors_1, descriptors_2, matches );
  double max_dist = 0; double min_dist = 100;

  //-- Quick calculation of max and min distances between keypoints
  for( int i = 0; i < descriptors_1.rows; i++ )
  { double dist = matches[i].distance;
    if( dist < min_dist ) min_dist = dist;
    if( dist > max_dist ) max_dist = dist;
  }

  //-- Draw only "good" matches (i.e. whose distance is less than 2*min_dist,
  //-- or a small arbitary value ( 0.02 ) in the event that min_dist is very
  //-- small)
  //-- PS.- radiusMatch can also be used here.


  std::vector< DMatch > good_matches;
  for( int i = 0; i < descriptors_1.rows; i++ )
  { if( matches[i].distance <= max(2*min_dist, 0.02) )
    { good_matches.push_back( matches[i]);}
  }
  //-- Draw only "good" matches
  Mat img_matches;
  drawMatches( frame, keypoints1, prevframe, keypoints2,
               good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
               vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );

  //-- Show detected matches

  imshow( "Good Matches", img_matches );
  if( (good_matches.size() >=20)){

        for( unsigned int i = 0; i < good_matches.size(); i++ )
        {

        }
  }

    }
    waitKey(0);
    return 0;
}

please help

thanks all