学习OpenCV——ORB简化版&Location加速版
根据前面surf简化版的结构，重新把ORB检测的代码给简化以下，发现虽然速度一样，确实能省好多行代码，关键是有
BruteForceMatcher
NB类型：class gpu::BruteForceMatcher_GPU
再加上findHomography，之后perspectiveTransform就可以location，但是这样速度很慢；
于是改动一下，求matches的keypoints的x与y坐标和的平均值，基本上就是对象中心！！！
以这个点为中心画与原对象大小相同的矩形框，就可以定位出大概位置，但是肯定不如透视变换准确，而且不具有尺度不变性。
但是鲁棒性应该更好，因为，只要能match成功，基本都能定位中心，但是透视变换有时却因为尺度变换过大等因素，画出很不靠谱的矩形框！
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/imgproc/imgproc.hpp"
#include
#include
#include
using namespace cv;
using namespace std;
char* image_filename1 = "D:/src.jpg";
char* image_filename2 = "D:/Demo.jpg";
int main()
{
Mat img1 = imread( image_filename1, CV_LOAD_IMAGE_GRAYSCALE );
Mat img2 = imread( image_filename2, CV_LOAD_IMAGE_GRAYSCALE );
int64 st,et;
ORB orb1(30,ORB::CommonParams(1.2,1));
ORB orb2(100,ORB::CommonParams(1.2,1));
vectorkeys1,keys2;
Mat descriptor1,descriptor2;
orb1(img1,Mat(),keys1,descriptor1,false);
st=getTickCount();
orb2(img2,Mat(),keys2,descriptor2,false);
et=getTickCount()-st;
et=et*1000/(double)getTickFrequency();
cout<<"extract time:"< matches;
//class gpu::BruteForceMatcher_GPU
BruteForceMatchermatcher;//BruteForceMatcher支持 > >
//FlannBasedMatcher matcher;不支持
st=getTickCount();
matcher.match(descriptor1,descriptor2,matches);
et=getTickCount()-st;
et=et*1000/getTickFrequency();
cout<<"match time:"<(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
imshow("match",img_matches);
cout<<"match size:"<pt1;
vectorpt2;
float x=0,y=0;
for(size_t i=0;isrc_cornor(4);
vectordst_cornor(4);
src_cornor[0]=cvPoint(0,0);
src_cornor[1]=cvPoint(img1.cols,0);
src_cornor[2]=cvPoint(img1.cols,img1.rows);
src_cornor[3]=cvPoint(0,img1.rows);
perspectiveTransform(src_cornor,dst_cornor,homo);
Mat img=imread(image_filename2,1);
line(img,dst_cornor[0],dst_cornor[1],Scalar(255,0,0),2);
line(img,dst_cornor[1],dst_cornor[2],Scalar(255,0,0),2);
line(img,dst_cornor[2],dst_cornor[3],Scalar(255,0,0),2);
line(img,dst_cornor[3],dst_cornor[0],Scalar(255,0,0),2);
/*
line(img,cvPoint((int)dst_cornor[0].x,(int)dst_cornor[0].y),cvPoint((int)dst_cornor[1].x,(int)dst_cornor[1].y),Scalar(255,0,0),2);
line(img,cvPoint((int)dst_cornor[1].x,(int)dst_cornor[1].y),cvPoint((int)dst_cornor[2].x,(int)dst_cornor[2].y),Scalar(255,0,0),2);
line(img,cvPoint((int)dst_cornor[2].x,(int)dst_cornor[2].y),cvPoint((int)dst_cornor[3].x,(int)dst_cornor[3].y),Scalar(255,0,0),2);
line(img,cvPoint((int)dst_cornor[3].x,(int)dst_cornor[3].y),cvPoint((int)dst_cornor[0].x,(int)dst_cornor[0].y),Scalar(255,0,0),2);
*/
circle(img,Point(x,y),10,Scalar(0,0,255),3,CV_FILLED);
line(img,Point(x-img1.cols/2,y-img1.rows/2),Point(x+img1.cols/2,y-img1.rows/2),Scalar(0,0,255),2);
line(img,Point(x+img1.cols/2,y-img1.rows/2),Point(x+img1.cols/2,y+img1.rows/2),Scalar(0,0,255),2);
line(img,Point(x+img1.cols/2,y+img1.rows/2),Point(x-img1.cols/2,y+img1.rows/2),Scalar(0,0,255),2);
line(img,Point(x-img1.cols/2,y+img1.rows/2),Point(x-img1.cols/2,y-img1.rows/2),Scalar(0,0,255),2);
imshow("location",img);
et=getTickCount()-st;
et=et*1000/getTickFrequency();
cout<<"location time:"<