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 = 400;
    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(1)
    {
        frame = cvQueryFrame( capture );
        cvtColor(frame, img_scene, CV_BGR2GRAY);
        if( !img_object.data || !img_scene.data )
        { std::cout<< " --(!) Error reading images " << std::endl; return -1; }

        //-- 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 = 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 < 2*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
        
        for( 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,5.0 );

        //-- 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
        namedWindow( "Good Matches & Object detection", WINDOW_NORMAL );
        imshow( "Good Matches & Object detection", img_matches );
        char c = cvWaitKey(1);
        if( c == 27 ) break;

    }
    return 0;
}