一，SIFT 函数接口    

构造函数：

重载操作符：

用SIFT进行特征点提取和匹配

参考：

#include"stdafx.h"
#include <iostream>
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/core/core.hpp"  
#include "highgui.h"  
#include "opencv2/imgproc/imgproc.hpp"  
#include "opencv2/features2d/features2d.hpp"  
#include "opencv2/xfeatures2d/nonfree.hpp"  
#include <opencv2/opencv.hpp>  //头文件
#include <opencv2/xfeatures2d.hpp>
#include <opencv2/opencv.hpp>  //头文件
#include <opencv2/xfeatures2d.hpp>
using namespace cv;  //包含cv命名空间
using namespace std;


int main() {


// 
// now, you can no more create an instance on the 'stack', like in the tutorial
// (yea, noticed for a fix/pr).
// you will have to use cv::Ptr all the way down:
//
cv::Ptr<Feature2D> f2d = xfeatures2d::SIFT::create();
//cv::Ptr<Feature2D> f2d = xfeatures2d::SURF::create();
//cv::Ptr<Feature2D> f2d = ORB::create();
// you get the picture, i hope..
Mat img_1 = imread("1.jpg");
Mat img_2 = imread("2.jpg");
/*测试是否能读取图片*/
/*imshow("1", img_1);
imshow("2", img_2);
waitKey(0);*/


//f2d->detectAndCompute(image, noArray(), key_points, descriptor);
//-- Step 1: Detect the keypoints:
std::vector<KeyPoint> keypoints_1, keypoints_2;
f2d->detect(img_1, keypoints_1);
f2d->detect(img_2, keypoints_2);

//-- Step 2: Calculate descriptors (feature vectors)    
Mat descriptors_1, descriptors_2;
f2d->compute(img_1, keypoints_1, descriptors_1);
f2d->compute(img_2, keypoints_2, descriptors_2);


//-- Step 3: Matching descriptor vectors using BFMatcher :
BFMatcher matcher;
std::vector< DMatch > matches;
matcher.match(descriptors_1, descriptors_2, matches);


//绘制匹配出的关键点
Mat img_matches;
drawMatches(img_1, keypoints_1, img_2, keypoints_2, matches, img_matches);
namedWindow("【match图】", 0);
imshow("【match图】", img_matches);
//等待任意按键按下
waitKey(0);




}