我正在尝试使用 DAISY 和 FlannBasedMatcher 在同一图像的两个视角之间进行特征匹配。
我认为甚至没有一个匹配是正确的。
注意：每次运行程序时我也会得到不同的结果，但我认为这是预期的行为，如下所述：FlannBasedMatcher 返回不同的结果
那么我做错了什么？为什么这些比赛如此糟糕？
输入图像
错误和不确定的结果
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/xfeatures2d.hpp>
#include <iostream>
#include <vector>
#include <stdio.h>
using namespace cv;
using std::vector;
const float nn_match_ratio = 0.7f; // Nearest neighbor matching ratio
const float keypoint_diameter = 15.0f;
int main(int argc, char ** argv){
// Load images
Mat img1 = imread(argv[1]);
Mat img2 = imread(argv[2]);
vector<KeyPoint> keypoints1, keypoints2;
// Add every pixel to the list of keypoints for each image
for (float xx = keypoint_diameter; xx < img1.size().width - keypoint_diameter; xx++) {
for (float yy = keypoint_diameter; yy < img1.size().height - keypoint_diameter; yy++) {
keypoints1.push_back(KeyPoint(xx, yy, keypoint_diameter));
keypoints2.push_back(KeyPoint(xx, yy, keypoint_diameter));
}
}
Mat desc1, desc2;
Ptr<cv::xfeatures2d::DAISY> descriptor_extractor = cv::xfeatures2d::DAISY::create();
// Compute DAISY descriptors for both images
descriptor_extractor->compute(img1, keypoints1, desc1);
descriptor_extractor->compute(img2, keypoints2, desc2);
vector <vector<DMatch>> matches;
// For each descriptor in image1, find 2 closest matched in image2 (note: couldn't get BF matcher to work here at all)
FlannBasedMatcher flannmatcher;
flannmatcher.add(desc1);
flannmatcher.train();
flannmatcher.knnMatch(desc2, matches, 2);
// ignore matches with high ambiguity -- i.e. second closest match not much worse than first
// push all remaining matches back into DMatch Vector "good_matches" so we can draw them using DrawMatches
int num_good = 0;
vector<KeyPoint> matched1, matched2;
vector<DMatch> good_matches;
for (int i = 0; i < matches.size(); i++) {
DMatch first = matches[i][0];
DMatch second = matches[i][1];
if (first.distance < nn_match_ratio * second.distance) {
matched1.push_back(keypoints1[first.queryIdx]);
matched2.push_back(keypoints2[first.trainIdx]);
good_matches.push_back(DMatch(num_good, num_good, 0));
num_good++;
}
}
Mat res;
drawMatches(img1, matched1, img2, matched2, good_matches, res);
imwrite("_res.png", res);
return 0;
}