OpenCV视屏跟踪

#include <stdio.h>
#include <iostream>
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/nonfree/nonfree.hpp"
using namespace cv;

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

    CvCapture* capture = cvCreateFileCapture( "sign3.mp4" );
    Mat img_object = imread( "pic3.jpg", CV_LOAD_IMAGE_GRAYSCALE );
    Mat frame = cvQueryFrame( capture );

    Mat img_scene;
    cvtColor(frame, img_scene, CV_BGR2GRAY);

    int minHessian = ;
    SurfFeatureDetector detector( minHessian );
    std::vector<KeyPoint> keypoints_object, keypoints_scene;
    detector.detect( img_object, keypoints_object );

    SurfDescriptorExtractor extractor;
    Mat descriptors_object, descriptors_scene;
    extractor.compute( img_object, keypoints_object, descriptors_object );

    FlannBasedMatcher matcher;
    std::vector< DMatch > matches;

    std::vector<Point2f> obj;
    std::vector<Point2f> scene;

    while()
    {
        frame = cvQueryFrame( capture );
        cvtColor(frame, img_scene, CV_BGR2GRAY);
        if( !img_object.data || !img_scene.data )
        { std::cout<< " --(!) Error reading images " << std::endl; return -; }

        //-- Step 1: Detect the keypoints using SURF Detector

        detector.detect( img_scene, keypoints_scene );

        //-- Step 2: Calculate descriptors (feature vectors)

        extractor.compute( img_scene, keypoints_scene, descriptors_scene );

        //-- Step 3: Matching descriptor vectors using FLANN matcher

        matcher.match( descriptors_object, descriptors_scene, matches );
        double max_dist = ; double min_dist = ;

        //-- Quick calculation of max and min distances between keypoints
        for( int i = ; 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 = ; i < descriptors_object.rows; i++ )
        {
            if( matches[i].distance < *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(-), Scalar::all(-),
            vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );

        //-- Localize the object

        for( int i = ; 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,5.0 );

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

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

        //-- Show detected matches
        namedWindow( "Good Matches & Object detection", WINDOW_NORMAL );
        imshow( "Good Matches & Object detection", img_matches );
        char c = cvWaitKey();
        if( c ==  ) break;

    }
    return ;
}