new

#include <stdio.h>
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/imgcodecs/imgcodecs.hpp"
#include <opencv2/videoio/videoio.hpp>
#include <opencv2/video/video.hpp>
#include "opencv2/xfeatures2d/nonfree.hpp"
#include "opencv2/xfeatures2d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/objdetect.hpp"
#include "opencv2/calib3d.hpp"
#include <stdlib.h>

using namespace cv;
using namespace cv::xfeatures2d;
FlannBasedMatcher matcher;
using namespace std;

Mat img_scene,img_object;

int main(int argc, char** argv )
{

    String imageName( "/home/zubair/Desktop/EXAMPLE/new12.jpg" );

       if( argc > 1)
    {
       imageName = argv[1];
    }

    img_object = imread(imageName,CV_LOAD_IMAGE_GRAYSCALE );
    //img_scene = imread(argv[2],CV_LOAD_IMAGE_GRAYSCALE );

    VideoCapture cap(0);
    if (!cap.isOpened())
     {
          cout << "Cannot access camera" << endl;
          return -1;
     }

    if ( !img_object.data )
    {
        printf("No object image \n");
        return -1;
    }

while(1)
    {


    //namedWindow("obj", WINDOW_AUTOSIZE );
    //namedWindow("scene",WINDOW_AUTOSIZE );
    //imshow("obj", img_object);
    //imshow("scene", img_scene);

    cap >> img_scene;

    if(img_scene.empty())
    {
        cout<<"no Frame in Image scene"<<endl;
        return -1;
    }

    imshow("image scene",img_scene);
    imshow("object image",img_object);

    if( waitKey(10) == 27 ) break;
    int minHessian = 400;

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

  std::vector<KeyPoint> keypoints_object, keypoints_scene;

  detector->detect( img_object, keypoints_object );
  detector->detect( img_scene, keypoints_scene );

  //-- Step 2: Calculate descriptors (feature vectors)
  Ptr<SURF> extractor = SURF::create();

  Mat descriptors_object, descriptors_scene;

  extractor->compute( img_object, keypoints_object, descriptors_object );
  extractor->compute( img_scene, keypoints_scene, descriptors_scene );

  //-- Step 3: Matching descriptor vectors using FLANN matcher
  FlannBasedMatcher matcher;
  std::vector< DMatch > matches;
  matcher.match( descriptors_object, descriptors_scene, matches );

  double max_dist = 0; double min_dist = 100;

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

  printf("-- Max dist : %f \n", max_dist );
  printf("-- Min dist : %f \n", min_dist );

  //-- Draw only "good" matches (i.e. whose distance is less than 3*min_dist )
  std::vector< DMatch > good_matches;

  for( int i = 0; i < descriptors_object.rows; i++ )
  { if( matches[i].distance < 3*min_dist )
     { good_matches.push_back( matches[i]); }
  }

  Mat img_matches;
  drawMatches( img_object, keypoints_object, img_scene, keypoints_scene,
               good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
               vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );

  //-- Localize the object
  std::vector<Point2f> obj;
  std::vector<Point2f> scene;

  for( unsigned int i = 0; i < good_matches.size(); i++ )
  {
    //-- Get the keypoints from the good matches
    obj.push_back( keypoints_object[ good_matches[i].queryIdx ].pt );
    scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt );
  }

  Mat H = findHomography( obj, scene, CV_RANSAC );

  //-- Get the corners from the image_1 ( the object to be "detected" )
  std::vector<Point2f> obj_corners(4);
  obj_corners[0] = cvPoint(0,0); obj_corners[1] = cvPoint( img_object.cols, 0 );
  obj_corners[2] = cvPoint( img_object.cols, img_object.rows ); obj_corners[3] = cvPoint( 0, img_object.rows );
  std::vector<Point2f> scene_corners(4);

  perspectiveTransform( obj_corners, scene_corners, H);

  //-- Draw lines between the corners (the mapped object in the scene - image_2 )
  line( img_matches, scene_corners[0] + Point2f( img_object.cols, 0), scene_corners[1] + Point2f( img_object.cols, 0), Scalar(0, 255, 0), 4 );
  line( img_matches, scene_corners[1] + Point2f( img_object.cols, 0), scene_corners[2] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );
  line( img_matches, scene_corners[2] + Point2f( img_object.cols, 0), scene_corners[3] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );
  line( img_matches, scene_corners[3] + Point2f( img_object.cols, 0), scene_corners[0] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );

  //-- Show detected matches
  imshow( "Good Matches & Object detection", img_matches );

}
    waitKey(10);
    return 0;
}