c++ - OpenCV Matcher のポイントの場所にアクセスするには?

Question

このFLANNマッチャーアルゴリズムを使用して、2つの画像の関心点を一致させています。コードは以下に表示されています)。

コードが一致するポイントのリストを見つける瞬間があります。

std::vector<DMatch> good_matches;

両方の写真でポイントのローカリゼーション (x、y) を取得したいと思います。ディスプレイスメント マップを作成するには。これらのポイントのローカリゼーションにアクセスするにはどうすればよいですか?

乾杯、

#include <stdio.h>
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/nonfree/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"

using namespace cv;

void readme();

/** @function main */
int main(int argc, char** argv) {
    if (argc != 3) {
        readme();
        return -1;
    }

    // Transform in GrayScale
    Mat img_1 = imread(argv[1], CV_LOAD_IMAGE_GRAYSCALE);
    Mat img_2 = imread(argv[2], CV_LOAD_IMAGE_GRAYSCALE);

    // Checks if the image could be loaded
    if (!img_1.data || !img_2.data) {
        std::cout << " --(!) Error reading images " << std::endl;
        return -1;
    }

    //-- Step 1: Detect the keypoints using SURF Detector
    int minHessian = 400;

    SurfFeatureDetector detector(minHessian);

    std::vector<KeyPoint> keypoints_1, keypoints_2;

    detector.detect(img_1, keypoints_1);
    detector.detect(img_2, keypoints_2);

    //-- Step 2: Calculate descriptors (feature vectors)
    SurfDescriptorExtractor extractor;

    Mat descriptors_1, descriptors_2;

    extractor.compute(img_1, keypoints_1, descriptors_1);
    extractor.compute(img_2, keypoints_2, descriptors_2);

    //-- Step 3: 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;
//      printf("-- DISTANCE =  [%f]\n", dist);
        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 2*min_dist )
    //-- 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 < 2 * min_dist) {
            good_matches.push_back(matches[i]);
        }
    }

    //-- Draw only "good" matches
    Mat img_matches;
    drawMatches(img_1, keypoints_1, img_2, keypoints_2, 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);

    for (int i = 0; i < good_matches.size(); i++) {
        printf("-- Good Match [%d] Keypoint 1: %d  -- Keypoint 2: %d  \n", i,
                good_matches[i].queryIdx, good_matches[i].trainIdx);
    }

    waitKey(0);

    return 0;
}

/** @function readme */
void readme() {
    std::cout << " Usage: ./SURF_FlannMatcher <img1> <img2>" << std::endl;
}