如何訪問OpenCV Matcher上的點位置？

Question

我正在使用此FLANN匹配器算法來匹配2張圖片中的興趣點，代碼顯示在下面）。

有當代碼找到匹配點列表的時刻：

std::vector<DMatch> good_matches; 

我想獲得在這兩張圖片的定位點（X，Y）。創建位移圖。 我怎樣才能訪問這些點本地化？

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; 
} 

Answer 1

matched_points1和2將在左和右圖像的對應點。然後，您可以在右圖中找到帶有idx1 = good_matches [i] .trainIdx的good_match索引，爲左圖找到idx2 = good_matches [i] .queryIdx。然後，只需將相應的點添加到matching_points向量中即可獲得匹配的x，y點向量。

long num_matches = good_matches.size(); 
vector<Point2f> matched_points1; 
vector<Point2f> matched_points2; 

for (int i=0;i<num_matches;i++) 
{ 
    int idx1=good_matches[i].trainIdx; 
    int idx2=good_matches[i].queryIdx; 
    matched_points1.push_back(points1[idx1]); 
    matched_points2.push_back(points2[idx2]); 
} 

現在你有兩個匹配點向量。我想這就是你要問的？